The energy was electric last week as thousands of attendees invaded MGM Grand along the Las Vegas Strip for the 3rd Annual Power Platform Community Conference (PPCC24).

From groundbreaking announcements to new features unveiled during keynotes from Microsoft’s Charles Lamanna, Corporate Vice President of Business Industry and Copilot, and Jeff Teper, President of Apps and Platforms, PPCC24 offered an electrifying three days of innovation and collaboration.

Lamanna kicked off day one with an eye-opening overview of Microsoft’s low-code superhero of today, Power Platform. With more than 48 million active users every month – surpassing the population of Spain – Power Platform has become the “one platform” for everyone, whether it’s for no code, low code or pro code. But what truly stole the show this year was Copilot – set to revolutionize how developers work, bringing automation dreams to life.

The future of low-code development is evolving, and at PPCC24, it was clear: Power Platform plus Copilot equals transformative potential for businesses across industries, signaling a new road ahead for citizen developers and Microsoft automation:

“Most people overestimate what they can do in one year and underestimate what they can do in ten years.”

Let’s dive into key announcements and takeaways from PPC24:

The Rise of AI and Natural Language in Power Platform

AI is more deeply integrated into Power Platform than ever before, with a major emphasis on natural language capabilities and intelligent apps. Here are some of the top features unveiled during the conference:

• Desktop Flows from Natural Language – Now in public preview, this feature enables users to generate desktop flows in Power Automate simply by using natural language. The barriers to automation just got lower for everyone, regardless of technical expertise.

• Power Automate AI Recording for Desktop Flows – Also in public preview, this “show and tell” experience allows users to record desktop flows, making RPA workflows easier for users of all skill levels. The AI will interpret recordings to generate automated processes, speeding up adoption and productivity.

• AI Agents for Copilot Studio – A game-changer for developers, AI agents will dynamically execute actions based on instructions and automatically handle workflow based on parameters. These agents can be trained and improved continuously, turning Copilot Studio into a true powerhouse for automation.

Coauthoring in Power Apps Now Generally Available

A highly anticipated feature from the Power Community, Co-Authoring in Power will beckon the next level of developer collaboration. This functionality allows up to 10 developers to collaborate in real time, editing apps simultaneously and a bringing new level of teamwork to app development.

As Charles Lamanna put it, “We are now all coauthors of this vision.” The seamless collaboration made possible through coauthoring will undoubtedly push the boundaries of what’s possible for low-code development.

The Road Ahead is Copilot-First

A standout theme from the conference was a Copilot-first vision for the future of low-code development. With tools like Copilot Studio set to be upgraded with GPT-4, the next generation of low-code technologies will be supported by AI agents that assist with tasks like solution design, data modeling, development, and visual design.

Perficient a Standout in Power Platform’s Future

As a leading Microsoft Solutions Partner, ranked 12th for Microsoft Power Platform partners, Perficient is thrilled to be at the forefront of this Community. From hosting a successful happy hour at Chez Bippy’s the night before the conference, to engaging with attendees at our booth—where we proudly supported donations to St. Jude’s Children’s Hospital—we’re excited to continue building on PPCC24 momentum. Our focus on helping organizations harness the full power of the latest Power Platform features to innovate faster and more intelligently will continue to help us lead the way.

While PPCC24 offered new announcements and innovations, it is only the beginning. As an award-winning Microsoft Solutions Provider, we’re committed to building groundbreaking solutions and bringing the robust capabilities of Power Platform to organizations everywhere. Whether it’s through AI-driven automation, real-time app coauthoring, or our continued work with Copilot, we’re dedicated to empowering businesses to innovate at scale.

Read more about our Power Platform practice here and stay tuned for upcoming events, workshops, and other exciting Power Platform activities!

For my first time attending the International Manufacturing Technology Show (IMTS), I must say it did not disappoint. This incredible event in Chicago happens every two years and is massive in size, taking up every main hall in McCormick Place. It was a combination of technology showcases, featuring everything from robotics to AI and smart manufacturing.

As a Digital Strategy Director at Perficient, I was excited to see the latest advancements on display representing many of the solutions that our company promotes and implements at the leading manufacturers around the globe. Not to mention, IMTS was the perfect opportunity to network with industry influencers as well as technology partners.

Oh, the People You Will Meet and Things You Will See at IMTS

Whenever you go to a show of this magnitude, you’re bound to run into someone you know. I was fortunate to experience the show with several colleagues, with a few of us getting to meet our Amazon Web Services (AWS) account leaders as well as Google and Microsoft.

The expertise of the engineers at each demonstration was truly amazing, specifically at one Robotic QA display. This robotic display was taking a series of pictures of automobile doors with the purpose of looking for defects. The data collected would go into their proprietary software for analysis and results. We found this particularly intriguing because we had been presented with similar use cases by some of our customers. We were so engrossed in talking with the engineers that our half-hour-long conversation felt like only a minute or two before we had to move on.

After briefly stopping to grab a pint—excuse me, picture—of the robotic bartender, we made our way to the Smart Manufacturing live presentation on the main stage. The ultra-tech companies presented explanations of how they were envisioning the future with Manufacturing 5.0 and digital twins, featuring big data as a core component.  It was reassuring to hear this, considering that it’s a strength of ours, thus reinforcing the belief that we need to continue focusing on these types of use cases. Along with big data, we should stay the course with trends shaping the industry like Smart Manufacturing, which at its roots are a combination of operations management, cloud, AI, and technology.

Goodbye IMTS, Hello Future Opportunities with Robotics, AI, and Smart Manufacturing

Overall, IMTS was certainly a worthwhile investment. It provided a platform to connect with potential partners, learn about industry trends, and strengthen our relationships with technology partners. As we look ahead to future events, I believe that a focused approach, leveraging our existing partnerships and adapting to the evolving needs of the manufacturing industry, will be key to maximizing our participation.

If you’d like to discuss these takeaways from IMTS Chicago 2024 at greater depth, please be sure to connect with our manufacturing experts.

Nowadays, AI is a crucial field with various frameworks like ML.NET that can be used to build amazing applications using pre-built models from cloud providers. It’s important to learn how these services work behind the scenes, how to create custom models, and understand how your application can interact with AI frameworks beyond just cloud providers or the source of the AI services.

How can I use ML Net?

ML Net can be used with Visual Studio 2019 or later, using any version of Visual Studio, and also can be used by Visual Studio Code, but only works on a Windows OS, Its prerequisites are:

• Visual Studio 2022 or Visual Studio 2019.
• .NET Core 3.1 SDK or later.

Image 1: Visual Studio installer, Installation Details contains the ML Net Model builder

Image 2: Visual Studio Context Menu

After adding the ML Net component to your project, you can see a wizard that allows you to set up your model as you need (Image 3).

Image 3: ML NET Wizard

Application Overview

The application starts with the weather Groups, every item contains a temperature range, a button to search the Historical data, and a forecast prediction (Image 4).

Image 4: Weather forecast main page.

The source of those groups is a table named Weather with the attributes:

• Id: primary key
• Description: that is the group description, you can see it as the title of the cards in image 4
• MinRange: Minimal temperature belongs to the group.
• MaxRange: Maximum temperature to belongs to the group.

The “History” button shows a table with all the historical data paginated. The historical data contains,  the date with format (yyyy-mm-dd),  the temperature, and if the day was cloudy (Image 5)

Image 5: Weather forecast historical page.

The predict option allows the users to generate their own prediction using ML Net through an API endpoint, the input data is the number of days from today that the user will predict and if the day will be cloudy (Image 6)

Image 6: Prediction page

The API result is the date, the group, and the percentage of probability that the date will belong to the group, also shows a table with the percentage of probability of every group.

Model

In the real world, there are lots of variables to keep in mind if you want to implement a Weather Forecast prediction app, such as wind speed, temperature, the season, humidity, if it was cloudy, etc.(2)

The scope of this approach is to see how ML Net can solve a custom model; therefore, a simple custom model was created, based on the temperature, and the season and if the day is cloudy, the model uses the weather as group of different forecasts, then the custom training model was designed as follow (Image 7):

• Weather (Id): Every grouper has an ID, so the label to predict it is the ID.
• Date: it is the feature of the date related to the weather
• IsCloudy: it’s a Boolean feature that indicates the relationship between weather and clouds.
• Season (Id): it is a feature that indicates the relationship between weather and season (Every season has an id)

Image 7: Training data section from ML Net wizard

You can get the data from Files, SQL Server databases, for this case, the data was collected from a View on SQL Server.

Project Architecture Overview

The weather forecast has 2 sites a front-end and a back-end, the data was stored in a SQL Server Database (Image 8). With this overall approach, the system was designed to separate the responsibilities of the business logic, the data, and the user experience.

Image 8: Sites and database

Front-end

You can find the app repository on GitHub using the following URL: https://github.com/joseflorezr/trainingangularversion

The front-end repository contains an angular 18 solution, which uses angular materials to help improve the user experience, and routing for navigation. The solution contains the following components (image 9):

• Forecast-header: The top component of the page, it shows the title with its style.
• Forecast-prediction: Contains the form for weather predictions and shows the results.
• Forecast results: Contains the historical data.
• Weather: Shows the groups of weather forecasts
• Services: Connects to the API to get weather, forecasts, and predictions
• Model: interfaces that map with the API

Image 9: Front-end components

Back-end

You can find the app repository on GitHub using the following URL: https://github.com/joseflorezr/WebApiMlNetWeatherForecast.

Image 10: Back End components

The API solution contains  the following projects:

• TestWebAPi: Web API with the endpoints, contains 3 controllers, Weather, forecast, and WeatherForecast. WeatherForecast is an abstract class with the logger and the use case reference injection.
• Business: Contains the classes that contain the business logic, based on the Use Case approach(4)
• Model: It is the abstraction of the domain objects like Weather, Forecast, Season, and predicted forecast
• Data: This library contains 2 parts:
  • The integration at the data level, the context with Entity Framework to get to the database.
  • The integration with ML Net, after being added to the solution, some  support files were  scaffolded with the same name but different descriptions, in this case, the file is MLForecastModel:
    • mbconfig: contains the wizard that helps to change the settings.
    • consumption: a partial class that allows interaction with the model.
    • evaluate: a partial class that allows to calculate of the metrics
    • mlnetl: this file contains the knowledge base; it is important to share the file at the  API level.
    • training: Adds the training methods that support the creation of the file.

Database Project(3)

The data was built abstracting the concepts of the Weather and Season as master entities with their description, otherwise Forecast it’s the historical table that contains the information for a specific date (1 row per day) the observation, that means, the temperature, the season id and then the weather id.

Visual Studio contains a database project that allows developers to create, modify, and deploy databases, and can run scripts after the deployment. To create the ML Net model, a View named WeatherForecast was used because it’s easier to connect to the ML Net Wizard.  The image 11 shows the relationship between the tables.

Image 11: Database diagram

Database projects can be deployed using the SQL Schema comparer tool, there is a post-build script that creates the data to the database model. For this app, a script was executed simulating forecast data from 1900-01-01 to 2024-06-04. The script uses random data, so the results must be different every time that you populate the forecast table.

WeatherForecast view concentrates the data used by ML Net to create the model.

API Project

The API project exposes endpoints that support getting the groups (Weather Controller), getting the historical Forecast data (Forecast Controller), and predict (Forecast Controller)

Image 12:  Web API Swagger

Note: The ML net file must be added as a resource of the API because the MLForecastModel class at the moment the API uses the prediction functionality, tries to look at the file on a specific path (it could be changed).

Image 13: ML Net file location

Model Project

Contains the DTOs that can be transferred to the Front-end, basically, the weather entity has the group description and the temperature ranges, the season contains the description of the starting and end months, the forecast has the temperature, date if the day was cloudy and id, PredictedForecast inherits from forecast and the score, and weather description was added (Image 14).

Image 14: Entities

Basically, ML Net  creates the MLForecastModel class, it contains the methods to use the prediction model (the result is different for the chosen scenario), but in general terms, the idea is to send an Input object (defined by ML Net) and receive results as follows:

• For a single object, use the Predict method, it will return the score for the predicted label.
• If you want to get the labels, use the GetLabels method, it will return all the labels as an IEnumerable.
• If you want to evaluate all labels, PredictAllLabels is the method, it will return a sorted IEnumerable with key-value pairs (label and score)
• If you want to map an unlabeled result, use the GetSortedScoresWithLabels, it will return a sorted IEnumerable with key-value pairs (label and score)

The PredictAsync Method (Image 15), creates the input object, starting with the user input (id, days, cloudy), it gets the projected date adds the days, and then finds the season ID based on the month (GetSeasonMethod). After the input project was complete, the chosen method to use was PredictAllLabels. In this case, the label is a Weather ID, so it was needed to get the Description from the Database for every given label.

Image 15: PredictAsync Implementation

Summary

• You can use ML NET to create your own Machine Learning models and use them as part of your API solution.
• There are multiple options (scenarios) to choose from according to your needs.
• Models can be created using diverse sources, such as Database objects, or files.

References

1. https://learn.microsoft.com/en-us/dotnet/machine-learning/how-does-mldotnet-work
2. https://content.meteoblue.com/en/research-education/specifications/weather-variables
3. https://visualstudio.microsoft.com/vs/features/ssdt/
4. https://medium.com/@pooja0403keshri/clean-architecture-a-comprehensive-guide-with-c-676beed5bdbb
5. https://learn.microsoft.com/en-us/aspnet/core/fundamentals/dependency-injection?view=aspnetcore-8.0

Computational complexity studies the efficiency of algorithms. It helps classify the algorithm in terms of time and space to identify the amount of computing resources needed to solve a problem. The Big Ω, and Big θ notations are used to describe the asymptotic behavior of an algorithm as a function of the input size. In computer science, computational complexity theory is fundamental to understanding the limits of how efficiently an algorithm can be computed.

This paper seeks to determine when an algorithm provides solvable solutions in a short com- putational time and to find those that generate solutions with long computational times that can be categorized as intractable or unsolvable, using these polynomial functions as a classical repre- sentation of computational complexity. Some mathematical notations to represent computational complexity, its mathematical definition from the perspective of function theory and predicate cal- culus, as well as complexity classes and their main characteristics to find polynomial functions will be explained. Mathematical expressions can explain the time behavior of a function and show the computational complexity. In a nutshell, we can compare the behavior of an algorithm over time with a mathematical function such as f (n), f (n²), etc.

In logic and algorithms, there has always been a search for how to measure execution time, calculate the computational time to store data, determine whether an algorithm generates a cost or a benefit in solving a problem, or design algorithms that generate a viable solution.

Asymptotic notations

What is it?

Asymptotic notation describes how an algorithm behaves over time, when its arguments tend to a specific limit, usually when they grow very large (tend to infinity). It is mainly used in the analysis of algorithms to show their efficiency and performance, especially in terms of execution time or memory usage as the size of the input data increases.

The asymptotic notation represents the behavior of an algorithm over time by making a com- parison with mathematical functions. The algorithm has a cycle while repeating different actions until a condition is fulfilled, it can be said that this algorithm has a behavior similar to a linear function, but if it has another cycle within the one already mentioned, it can be compared to a quadratic function.

How is an asymptotic notation represented?

Asymptotic notations can be expressed in 3 ways:

• O(n): The term ‘Big O’ or BigO refers to an upper limit on the execution time of an algorithm. It is used to describe the worst-case It is used to describe the worst-case scenario. For example, if an algorithm is O(n²) in the worst-case scenario, its execution time will increase proportionally to n² where the n is the input size.
• Ω(n): The ‘Big Ω’ or BigΩ, describes a minimum limit on the execution time of an algorithm and is used to describe the best-case scenario. The algorithm has the behavior of Ω(n), which means that in the best case, the execution time of the algorithm will grow at least proportionally a n.
• Θ(n): ‘Big Θ’ or BigΘ, are to both an upper and a lower bound of the time behavior of an algorithm. It is used to explain that, regardless of the case, the execution time of the algorithm increases proportionally to the specified value. For example, if an algorithm is Θ(nlogn), your execution time will increase proportionally to nlogn at both ends.

In a nutshell, asymptotic notation is a mathematical representation of computational com- plexity expressed in terms of computational complexity. Now, if we express in polynomial terms an asymptotic notation, it allows us to see how the computational cost increases as a reference variable increases. For example, let’s evaluate a polynomial function f (n) = n + 7 to conclude that this function has a linear growth. Compare this linear function with a second one given what g(n) = n³ − 2, the function g(h) will have a cubic growth when n is larger.

Figure 1: f (n) = n + 7 vs g(n) = n³ − 2

From a mathematical point of view, it can be stated that:

The function f (n) = O(n) and that the function g(n) = O(n³)

Computational complexity types

Finding an algorithm that solves a problem efficiently is crucial in analyzing algorithms. To achieve this we must be able to express the algorithm’s behavior in functions, for example, if we can express the algorithm as the polynomial f (n) function, a polynomial time can be set to determine the algorithmic efficiency. In general, a good design of an algorithm depends on whether it runs in polynomial time or less.

Frequency counter and arithmetic sum and bounding rules

To express an algorithm as a mathematical function and know it is execution time, it is neces- sary to find an algebraic expression that represents the number of executions or instructions of the algorithm. The frequency counter is a polynomial representation that has been worked on throughout the topic of computational complexity. with some simple examples in Csharp on how to calculate the computational complexity of some algorithms. Use the Big O, because expresses computational complexity in the worst-case scenario.

Computational complexity Constant

Analyze the function that adds 2 numbers and returns the result of the sum:

With the Big O notation for each of the instructions in the above algorithm, the number of times each line of code is executed can be determined. In this case, each line is executed only once. Now, to determine the computational complexity or the Big O of this algorithm, the complexity for each of the instructions must be summed up:

O(1) + O(1) = O(2)

The constant value is equal 2, the polynomial time of the algorithm is constant, i.e. O(1).

Polynomial Computational Complexity

Now let’s look at another example with a slightly more complex algorithm. We need to traverse an array containing the numbers from 1 to 100 and the total sum of the whole array is required:

In the sequence of the algorithm, lines 2 and 6 are executed only once, but lines 3 and 4 will be repeated n times, until reaching 100 iterations (n = 100 the size of the array), to calculate the computational cost of this algorithm, the following is done:

O(1) + O(n) + O(n) + O(1) = O(2n + 2)

From this result, it can be stated that the algorithm is executed in time lineal given that O(2n + 2) ≈ O(n). Let’s analyze another algorithm, similar but with two cycles one after the other. These algo- rithms are those whose execution time depends on two variables, n and m, linearly. This indicates that the length of the algorithm is proportional to the sum of the sizes of two independent inputs. The computational complexity for this type of algorithm is O(n + m).

In this algorithm, the two cycles are independent since the first while represents n + 1 times while the second while represents m + 1, being n ̸= m. Therefore, the computational cost is given by:

O(7) + O(2n) + O(2m) ≈ O(n + m)

Exponential computational complexity

For the third example, the computational cost for an algorithm containing nested cycles is analyzed:

The conditions in a while (while) and do-while (do while) cycles are executed n + 1 times, as compared to a foreach cycle. These loops do one additional step: validate the condition to end the loop. In line number 7, by repeating n times and doing its corresponding validation, the computational complexity at this point is n(n + 1). In the end, the result of the computational complexity of this algorithm would result in the following:

O(6) + O(4n) + O(2n²) = O(2n² + 4n + 6) ≈ O(n²)

Logarithmic computational complexity

• Logarithmic Complexity in base 2 (log₂(n)): Algorithms with logarithmic complexity O(logn) grow very slowly compared to other complexity types such as O(n) or O(n²). Even for large inputs, the number of trades does not increase Let us analyze the following algorithm:

Using a table, let us analyze the step-by-step execution of the algorithm proposed above:

Table 1: Logarithmic loop algorithm execution

If you examine the sequence in Table reftab:tab1, you can see that their behavior has a logarithmic correlation. A logarithm is the power that must be raised to get another number. For example, log₁₀100 = 2 because 10² = 100. Therefore, it is clear that the base 2 must be used for the proposed algorithm:

64/2 = 32

32/2 = 16

16/2 = 8

8/2 = 4

4/2 = 2

2/2 = 1

It can be calculated that log₂64 = 6, which means that the six (6) loop has been executed six (6) times (i.e. when k takes values {0, 1, 2, 3, 4, 5}). This conclusion confirms that the while loop of this algorithm is log₂(n), and the computational cost is shown as:

O(1) + O(1) + O(log₂(n) + 1) + O(log₂(n)) + O(log₂(n)) + O(1)

= O(4) + O(3log₂(n))

O(4) + O(3log₂(n)) ≈ O(log₂(n))

• Logarithmic complexity (nlog(n)): Algorithms O(nlog(n)) have an execution time that increases in proportion to the product of the input size n and the logarithm of n. This indicates that the execution time does not double if the input size is doubled, on the contrary, it increases less significantly due to the logarithmic factor. This type of complexity has a lower efficiency than O(n²) but higher than O(n).

O(2 ∗ (n/2)) + O(1) ≈ O(nlog(n))

Analyzing the algorithm proposed above, mentioning the merge sort algorithm, the algorithm performs a similar division, but instead of sorting elements, it counts the possible divisions into subgroups. The complexity of this algorithm is O(nlog(n)) due to recursion and n operations are performed at each recursion level until the base case is reached.

Finally, in a summary graph, you can see, the behavior of the number of operations performed by the functions based on their computational complexity.

Example

An integration service is periodically executed to retrieve customer IDs associated with four or more companies registered with a parent company. The process performs individual queries for each company, accessing various databases that use different persistence technologies. As a result, an array of data containing the customer IDs is generated without checking or removing possible duplicates.

In this case, the initial approach would involve comparing each employee ID with all other elements in the array, resulting in a quadratic number of comparisons, i.e., O(n²):

In a code review, the author of this algorithm will be advised to optimize the current approach due to its inefficiency. To solve the problems related to nested loops, a more efficient approach can be taken by using a HashSet. Here is how to use this object to improve performance, reducing complexity from O(n²) to O(n):

Currently, in C# you can use an object called IEnumerable, which allows you to perform the same task in a single line of code. But in this approach, several clarifications must be made:

• Previously, it was noted that a single line of code can be interpreted as having O(1) complex- ity. In this case, it is different because the Distinct function traverses the original collection and returns a new sequence containing only the unique elements, removing any duplicates using a HashSet, which, as mentioned earlier, results in O(n) complexity.
• The HashSet also has a drawback: in the worst case, when collisions are frequent, the complexity can degrade to O(n²). However, this is extremely rare and typically depends on the quality of the hash function and the characteristics of the data in the collection.

The correct approach should be:

Conclusions

In general, we can reach three important conclusions about computational complexity.

• To evaluate and compare the efficiency of various algorithms, computational complexity is essential. Helps to understand how the execution time or resource usage (such as memory) of an algorithm increases with input size. This analysis is essential for choosing the most appropriate algorithm for a particular problem, especially when working with significant amounts of data.
• Algorithms with lower computational complexity can improve system performance signifi- cantly. For example, the choice of an algorithm O(nlogn) instead of one O(n2) can have a significant impact on the amount of time required to process large amounts of data. Ef- ficient algorithms are essential to ensure that the system is fast and scalable in real-world applications such as search engines, image processing, and big data analytics.

Figure 2: Operation vs Elements

• Understanding computational complexity helps developers and data scientists to design and optimize algorithms. It allows for finding bottlenecks and performance improvements. By adapting the algorithm design to the specific needs of the problem and the constraints of the execution environment, computational complexity analysis allows informed trade-offs between execution time and the use of other resources, such as memory.

References

• Roberto Flórez Algoritmia Básica, Second Edition, Universidad de Antioquia, 2011.
• Thomas Mailund. Introduction to Computational Thinking: Problem Solving, Algorithms, Data Structures, and More, Apress, 2021.

A major energy and utilities supplier has become the latest victim in a growing list of organizations targeted by cyberattacks. Without a quick response to an attack like this, energy companies can risk exposing customer data, cutting off energy supply, slowing or completely stopping operations, and more. 

According to the Department of Energy, the recent incident was responded to quickly, and had minimal lasting impact. However, these attacks are becoming increasingly frequent across industries, and the risks continue to grow. Let’s focus on one of the most common types of cybercrime: ransomware. 

Are Your Systems Susceptible to Malware? 

Ransomware attacks are pervasive, affecting various sectors including organizations like Colonial Pipeline, JBS Foods, and Kaseya. The most frequently targeted industries range from energy and finance to healthcare and entertainment. Malicious software, better known as malware, compromises network integrity by gaining access through phishing, stolen passwords, and other vulnerabilities. 

Ransomware-as-a-Service is a cybercrime business model made possible via modular business models with low barriers to entry, creating a wide market of perpetrators. These individuals are divided into developers who create the malware and affiliates who initiate the attacks, with profits split between them. 

It is crucial to be vigilant, with the most common defense being routine basic cybersecurity hygiene, such as implementing multi-factor authentication. Other tactics include adopting Zero Trust principles and preparing for potential attacks to minimize impact. While a good defense is wise, it is still essential to have a strong relationship between the government and private sector, with collaboration being of utmost importance. Companies must share information about breaches and their efforts to disrupt infrastructure with the support of law enforcement. 

Three Simple Ways to Prevent Cyberattacks 

Now that we have identified what makes malware like ransomware possible, let us address the best ways to avoid becoming a victim. We have broken the solution down into a few simple steps: 

1. Be prepared with a recovery plan – Make it incredibly challenging to access and disrupt your system. If you make an attack economically unfeasible, you have already avoided the threat. The goal is to avoid paying the ransom for privileges that might not be returned or using keys provided by attackers to regain access. While restoring corrupted systems can be burdensome, it is better than the alternative. 

1. Limit the scope of damage – By limiting privileged access roles, you reduce the number of entry points for attackers to acquire access to critical components of your business. If they can only gain access to pieces rather than the entire system, it will deter attackers from pursuing an escalated attack. 

1. Challenge cybercriminals as much as possible – This step should not interfere with steps 1 or 2, but it is essential to create as much friction as possible for potential attacks. Make it an uphill battle for intruders attempting to gain remote access, emails, endpoints, or accounts. If they do manage to get in, ensure they cannot escalate their privileges by implementing robust detection and response capabilities. 

Perficient’s team of experts is well-versed in these incidents and what can be done to prevent them. If you would like to begin mounting more serious defenses, explore our energy industry expertise and browse the many technology partners with which we work to give companies confidence in their security, like Microsoft. 

The Power Platform Community Conference 2024 in Las Vegas is fast approaching, and it’s shaping up to be one of the most impactful events of the year for anyone involved in digital transformation. Whether you’re a seasoned professional or just getting started with Microsoft’s Power Platform, this conference offers unparalleled opportunities to learn, connect, and grow. At Perficient, we’re excited to share our expertise, showcase our success stories, and connect with you to explore how we can help you maximize your Power Platform investment. Here’s everything you need to know to make the most of this conference, from what to expect to why you should engage with Perficient.

What is the Power Platform Community Conference?

The Power Platform Community Conference (PPCC) is the premier event for professionals who use or are interested in Microsoft’s Power Platform. This annual gathering brings together thousands of developers, business leaders, and technology enthusiasts from around the world to explore the latest trends, tools, and best practices in Power Platform. PPCC 2024 is set to showcase cutting-edge AI innovations, building on the success of previous years. It offers more than 150 sessions and keynotes, along with 20 hands-on workshops, and opportunities to connect with and gain insights from Microsoft thought leaders, product experts and developers, MVPs, and peers.

Key Takeaways from Last Year’s Conference

The 2nd annual Power Platform Community Conference in 2023 was a major success, highlighting the growing momentum behind low-code development. Some key takeaways include:

• Low-Code Momentum: The 2023 conference underscored the rapid expansion of the low-code market, with Power Platform playing a central role in enabling organizations to innovate quickly and efficiently.
• AI-Powered Solutions: There was a significant focus on integrating AI with Power Platform, particularly through tools like AI Builder and Power Automate. These advancements are helping organizations automate more complex tasks, driving efficiency, and reducing manual work.
• Community and Collaboration: The strength of the Power Platform community was a key theme, with thousands of professionals collaborating to share insights, solutions, and best practices.

What’s New for the 2024 Conference?

The 2024 conference will build on these themes, with an even stronger focus on AI-driven innovation. Microsoft plans to unveil several new AI features designed to help users automate more complex tasks and gain deeper insights from their data. The conference will highlight how generative AI advancements can be integrated seamlessly with existing Power Platform solutions to enhance productivity and efficiency.

This year, you can expect:

• Showcasing AI Innovations: New AI capabilities in Copilot Studio, Power Automate, Power BI, and AI Builder that simplify the implementation of intelligent automation and analytics solutions.
• Hands-On Labs and Networking: Continued opportunities to engage directly with the technology through hands-on labs and to connect with other professionals and experts in the field.
• Expert-Led Sessions: Sessions led by industry experts focused on how AI is transforming the approach to digital transformation.

For more details on what to expect from this year’s conference, check out Microsoft’s announcement here.

Getting Registered

To register for the Power Platform Community Conference, visit the official conference registration page. Full conference passes start at $1,849 and will be raised to $1,899 after August 27^th. You can add on one, two, or three full-day workshops for additional costs.

Once registered, take some time to plan your conference experience by reviewing the agenda and identifying which sessions align with your current projects or areas of interest.

Why Perficient Leads in Power Platform Solutions

At Perficient, our passion for Power Platform stems from its transformative impact across various industries. We’ve developed a proven track record, backed by 30+ certified experts and over 50 successful enterprise projects, delivering tangible results for our clients. Whether it’s implementing a Center of Excellence (COE) for a global auto manufacturer or building an automation program for a healthcare provider, our diverse industry experience allows us to craft tailored solutions that address unique business challenges.

We understand that every organization is at a different stage of its Power Platform journey. Whether you’re just starting or looking to optimize, our solutions and workshops are designed to align with your organization’s maturity level, ensuring you maximize your Power Platform investment.

Why Talk to Us at PPCC24

1. Custom Solutions for Unique Challenges: We tailor our Power Platform solutions to meet your specific business needs, from app development to automation and data analytics.
2. Deep Industry Insights: Our extensive experience across industries equips us with the insights needed to leverage Power Platform for addressing sector-specific challenges.
3. Commitment to Long-Term Success: Beyond implementation, we offer ongoing support, maintenance, and optimization to ensure your Power Platform environment continues to deliver value as your business grows.

By connecting with Perficient at PPCC24, you’re not just getting a solution; you’re gaining a partner committed to your success.

We’re looking forward to the Power Platform Community Conference and hope to see you there. Be sure to visit us at booth #134, where you can learn more about our success stories, discuss your specific challenges, and discover how Perficient can help you harness the full potential of Power Platform. Let’s work together to turn your vision into reality.

For more information about our Power Platform capabilities, visit Perficient’s Power Platform page.

VMware (Broadcom) has discontinued their VMware partner resell program. This announcement forces customers to move forward with one of three options:

1. Buy directly from VMware,
2. Migrate workloads to another hypervisor, or
3. Make a platform change.

For many VMware customers, the price changes were abrupt, while others have the luxury of taking a little more time to explore their options.

The Cloud Advantage

As organizations reassess their IT strategies, the shift toward cloud architectures is becoming increasingly attractive. Cloud solutions, built specifically for the cloud environment, offer unparalleled flexibility, scalability, and cost efficiency. They allow businesses to take full advantage of modern infrastructure capabilities without being locked into the escalating costs of traditional on-premises solutions.

Making the Transition

At Perficient, we understand the complexities and challenges associated with such a significant transition. Our expertise in cloud consulting and implementation positions us as the ideal partner to help you navigate this critical shift. Our consultants have developed a comprehensive and flexible plan to assist you in maximizing the efficiency of your platform change.

Comprehensive Assessment and Strategy Development

Our team begins with a thorough assessment of your current IT infrastructure, evaluating the specific impact of the VMware cost increase on your operations. We then develop a tailored strategy that aligns with your business goals, ensuring a smooth and cost-effective transition to cloud solutions.

Migration Services

Moving from a VMware-based infrastructure to a cloud environment can be complex. Our migration services ensure a seamless transition with minimal disruption to your business operations. We employ best practices and proven methodologies to migrate your workloads efficiently and securely.

Ongoing Support and Operational Efficiency

Post migration, we provide ongoing support to ensure your cloud environment operates at peak efficiency. Our team continuously monitors and optimizes your infrastructure, helping you to maximize the return on your cloud investment.

Cost Management and Optimization

One of the key advantages of cloud migration is the potential for significant cost savings and licensing cost avoidance. Our cost management services help you to leverage cloud features to reduce expenses, such as auto-scaling, serverless computing, and efficient resource allocation.

Embracing the Cloud

Perficient stands ready to guide you through this transition, providing the expertise, tools, and support necessary to successfully navigate this change. Together, we can turn this challenge into a transformative opportunity for your business.

To learn more about how these changes might impact your organization and explore our detailed strategy for a smooth transition, visit our cloud page for further insights. Our team is here to help you every step of the way.

In the realm of enterprise integration, choosing the right platform is crucial for ensuring seamless connectivity between diverse applications and systems. Azure Integration Services (AIS) and MuleSoft are two prominent players in this field. Azure Integration Services is a cloud-based integration platform provided by Microsoft, while MuleSoft is an integration platform that allows developers to connect applications, data, and devices. While both offer robust capabilities, Azure Integration Services provides distinct advantages that can be pivotal for businesses looking to optimize their integration strategies. Here are five major benefits of AIS over MuleSoft.

1. Seamless Integration with Microsoft Ecosystem

One of the standout benefits of Azure Integration Services is its seamless integration with the Microsoft ecosystem. AIS is designed to work natively with other Microsoft products and services such as Azure, Office 365, Dynamics 365, and Power Platform. This native compatibility ensures a smoother and more efficient integration process, reducing the need for custom connectors and simplifying the overall integration architecture. This compatibility provides a sense of reassurance to the audience, knowing that their existing Microsoft investments will seamlessly integrate with AIS.

Integration capabilities don’t stop there – AIS can integrate with all kinds of other systems including SaaS platforms, existing on-premises API’s, commerce platforms, banking platforms, and more.  Additionally, AIS supports more than .Net – you can also integrate with Java, Node, Python and many other technologies.

2. Comprehensive and Unified Offering

Azure Integration Services offers a comprehensive and unified suite of integration tools, including Azure Logic Apps, Azure Service Bus, Azure API Management, and Azure Event Grid. This unified approach allows businesses to address a wide range of integration needs within a single platform, streamlining management and reducing the complexity associated with using multiple tools. This versatility and adaptability of AIS’s suite of tools instills confidence in the audience about the platform’s ability to meet their diverse integration needs.

3. Scalability and Performance

Azure Integration Services leverages the global infrastructure of Microsoft Azure, ensuring high scalability and performance for enterprise-grade integrations. AIS can handle large volumes of data and transactions with ease, providing reliable and fast performance across various integration scenarios. MuleSoft, although scalable, may require more effort to achieve the same level of performance, particularly when dealing with complex and high-volume integrations.

4. Cost-Effectiveness

Cost is a critical factor for many organizations when choosing an integration platform. Azure Integration Services offers a more cost-effective solution compared to MuleSoft, primarily due to its consumption-based pricing model. Businesses pay only for the resources they use, allowing for better cost control and budgeting. Additionally, AIS often incurs significantly lower licensing and maintenance costs, making it an attractive option for organizations looking to optimize their IT expenditure.

5. Enhanced Security and Compliance

Security and compliance are top priorities for any integration platform. Azure Integration Services benefits from Azure’s robust security features and compliance certifications. With AIS, businesses can leverage advanced security measures such as encryption, identity and access management, and threat protection, ensuring that their integrations are secure and compliant with industry standards. While MuleSoft also offers strong security features, AIS’s integration with Azure’s comprehensive security framework provides an added layer of protection and peace of mind.

Conclusion

Azure Integration Services stands out as a powerful and cost-effective integration platform, offering seamless integration with the Microsoft ecosystem, a comprehensive suite of tools, high scalability and performance, cost efficiency, and enhanced security and compliance. For businesses looking to streamline their integration processes and leverage the full potential of their existing Microsoft investments, AIS presents a compelling choice over MuleSoft.

Contact us to learn more about how we can help you maximize your investment in Azure!

In the modern digital landscape, efficient collaboration and streamlined workflows are proven elements of successful project management. Integrating GitHub repositories with Azure Storage proves to be a robust solution for the management of project files in the cloud. Whether you’re a developer, a project manager, or a technology enthusiast, understanding how to push files from a GitHub repository to an Azure Storage container can significantly enhance your productivity and simplify your development process. In this comprehensive guide, we’ll explore the steps required to achieve this seamless integration.
You must be wondering why, although the files already exist in the repository, we are sending them from a GitHub repository to an Azure Storage container. While GitHub repositories are excellent for version control and collaboration, they might not be optimized for certain types of file storage and access patterns. Comparatively, Azure Storage provides a scalable, high-performance solution specifically designed for storing various types of data, including large files, binaries, and media assets.

By transferring files from a GitHub repository to an Azure Storage container, you can leverage Azure’s robust infrastructure to enhance scalability and optimize performance, especially in the below scenarios:      

• Large File Storage
• High Availability and Redundancy
• Access Control and Security
• Performance Optimization

Understanding the Solution

Before we dive into the practical steps, let’s gain a clear understanding of the solution we’re implementing:

1. GitHub Repository: This is where your project’s source code resides. By leveraging version control systems like Git and hosting platforms like GitHub, you can collaborate with team members, track changes, and maintain a centralized repository of your project files.
2. Azure Storage: Azure Storage provides a scalable, secure, and highly available cloud storage solution. By creating a storage account and defining containers within it, you can store a variety of data types, including documents, images, videos, and more.
3. Integration: We’ll establish a workflow to automatically push files from your GitHub repository to an Azure Storage container whenever changes are made. This integration automates deployment, ensuring synchronization between your Azure Storage container and GitHub repository. This not only unlocks new possibilities for efficient cloud-based file management but also streamlines the development process.

Prerequisites

1. Basic Knowledge of Git and GitHub: Understanding the fundamentals of version control systems like Git and how to use GitHub for hosting repositories is essential. Users should be familiar with concepts such as commits, branches, and pull requests.

2. Azure Account: Readers should have access to an Azure account to create a storage account and containers. If they don’t have an account, they’ll need to sign up for one.

3. Azure Portal Access: Familiarity with navigating the Azure portal is helpful for creating and managing Azure resources, including storage accounts.

4. GitHub Repository, Access to GitHub Repository Settings, and GitHub Actions Knowledge: Readers should have a GitHub account with a repository set up for deploying files to Azure Storage. Understanding how to access and modify repository settings, including adding secrets, is crucial for configuring the integration. Additionally, familiarity with GitHub Actions and creating workflows is essential for setting up the deployment pipeline efficiently.

5. Azure CLI (Command-Line Interface) Installation: Readers should have the Azure CLI installed on their local machine or have access to a terminal where they can run Azure CLI commands. Instructions for installing the Azure CLI should be provided or linked to.

6. Understanding of Deployment Pipelines: A general understanding of deployment pipelines and continuous integration/continuous deployment (CI/CD) concepts will help readers grasp the purpose and functionality of the integration.

7. Environment Setup: Depending on the reader’s development environment (Windows, macOS, Linux), they may need to make adjustments to the provided instructions. For example, installing and configuring Azure CLI might differ slightly across different operating systems.

Let’s Start from Scratch and See Step-By-Step Process to Integrate GitHub Repositories with Azure Storage

Step 1: Set Up Azure Storage Account

1. Sign in to Azure Portal: If you don’t have an Azure account, you’ll need to create one. Once you’re signed in, navigate to the Azure portal. – “portal.azure.com/#home”
        a. Create a Storage Account: In the Azure portal, click on “Create a resource” and search for “Storage account”. Click on “Storage account – blob, file, table, queue” from the search results. Then, click “Create”.
   
   
   

2. Configure Storage Account Settings: Provide the required details such as subscription, resource group, storage account name, location, and performance tier. For this guide, choose the appropriate options based on your preferences and requirements.
   
   
   

3. Retrieve Access Keys: Once the storage account is created, navigate to it in the Azure portal. Go to “Settings” > “Access keys” to retrieve the access keys. You’ll need these keys to authenticate when accessing your storage account programmatically.
   Note: Click on the show button to copy the Access key.

Step 2: Set Up GitHub Repository

1. Create a GitHub Account: If you don’t have a GitHub account, sign up for one at “github.com”

2. Create a New Repository: Once logged in, click on the “+” icon in the top-right corner and select “New repository”. Give your repository a name, description, and choose whether it should be public or private. Click “Create repository”.
   
   
   

3. Clone the Repository: After creating the repository, clone it to your local machine using Git. You can do this by running the following command in your terminal or command prompt:
   Command:

   git clone https://github.com/your-username/your-repository.gi

Note: Replace ‘your-username’ with your GitHub username and ‘your-repository’ with the name of your repository.

Step 3: Push Files to GitHub Repository

1. Add Files to Your Local Repository: Place the files you want to push to Azure Storage in your machine’s local repository directory.
   

2. Stage and Commit Changes: In your terminal or command prompt, navigate to the local repository directory and stage the changes by running:
       Command:

   git add .

    Then, commit the changes with a meaningful commit message:
      Command:

   git commit -m "Add files to be pushed to Azure Storage

3. Push Changes to GitHub: Finally, push the committed changes to your GitHub repository by running:
        Command: 

   git push origin main

     Note: Replace `main` with the name of your branch if it’s different.

Verify Files in GitHub: Check in your GitHub account file has been uploaded.



Step 4: Push Files from GitHub to Azure Storage

1. Install Azure CLI: If you haven’t already, install the Azure CLI on your local machine.
     Note: You can find installation instructions –  

   https://docs.microsoft.com/en-us/cli/azure/install-azure-cli

2. Authenticate with Azure CLI: Open your terminal or command prompt and login to your Azure account using the Azure CLI:
    Command:  

   az login

   Follow the prompts to complete the login process.

   

3. Upload Files to Azure Storage: Use the Azure CLI to upload the files from your GitHub repository to your Azure Storage container:
      Command:
   

   az storage blob upload-batch --source <local-path> --destination <container-name> --account-name <storage-account-name> --account-key <storage-account-key>
   
   

Note: Replace `<storage-account-name>` and `<storage-account-key>` with the name and access key of your Azure Storage account, respectively. Replace `<container-name>` and `<local-path>` with your container name and the local path to your repository directory, respectively.

Step 5: Verify Deployment

Once the workflow is complete, navigate to your Azure Storage container. You should see the files from your GitHub repository synchronized to the container. Verify the integrity of the files and ensure that the deployment meets your expectations.

Conclusion

By following these steps, you’ve successfully set up a seamless integration between your GitHub repository and Azure Storage container. This integration automates pushing files from your repository to the cloud, enabling efficient collaboration and simplified project management. Embrace the power of automation, leverage the capabilities of GitHub Actions and Azure Storage, and unlock new possibilities for your development workflow. Happy coding

In today’s dynamic digital landscape, businesses continually seek ways to streamline operations, boost productivity, and surge ahead of the competition. Microsoft Cloud Solution Providers (CSPs) play a central role in aiding organizations to achieve these aspirations. Let’s explore how CSPs deliver unparalleled value to their customers.

Tailored Solutions for Unique Needs

Every business possesses distinct requirements. Microsoft CSPs understand this and offer tailored cloud solutions to meet the specific needs of each organization. Whether implementing Azure services, Office 365, or Dynamics 365, CSPs provide expert guidance to ensure that businesses leverage the right tools for their unique circumstances.

Cost Efficiency and Flexibility

Working with a Microsoft CSP brings the significant advantages of cost efficiency and flexibility. CSPs provide various subscription & procurement models, allowing businesses to scale their services up or down as per demand.  This adaptability ensures that companies only pay for what they use, optimizing their IT spend and avoiding unnecessary expenses.  These subscription models are more flexible than traditional Enterprise Agreements and typically do not have the minimum seat requirements that EA’s have.

Seamless Integration and Migration

Migrating to the cloud can be a daunting prospect. However, CSPs have the expertise to ensure a smooth transition, minimizing disruptions to business operations. They handle everything from planning and execution to integration with existing systems, ensuring businesses can continue to operate efficiently during the migration process.  Combined with 24×7 managed support, CSPs can handle these needs via white-glove treatment.

Enhanced Security and Compliance

Security and compliance are primary concerns for businesses today. Microsoft CSPs bring a wealth of knowledge in implementing robust security measures and ensuring compliance with industry standards and regulations. They utilize advanced security features like multi-factor authentication, data encryption, security event monitoring, and regular security audits to protect sensitive information and maintain regulatory compliance.

Continuous Support and Managed Services

CSPs offer continuous support and managed services, ensuring businesses can access expert assistance whenever needed. From troubleshooting technical issues to providing ongoing maintenance and updates, CSPs act as an extended IT department, allowing businesses to focus on their core activities without worrying about IT management.

Innovation and Future-Readiness

Staying updated with the latest technological advancements is crucial for business growth. Microsoft CSPs keep businesses at the forefront of innovation by providing access to the latest cloud technologies and solutions. They help companies adopt new tools and features as they become available, ensuring that businesses are always future-ready.  CSPs often have a variety of engagements available to implement POC’s, facilitate knowledge transfer & adoption needs, and can also bring in full implementation teams to build new innovative solutions including AI readiness, landing zones, and product integration.

Conclusion

Microsoft Cloud Solution Providers are invaluable partners in the digital transformation journey. They bring tailored solutions, cost efficiency, seamless integration, enhanced security, continuous support, and innovation to businesses of all sizes. By partnering with a CSP, organizations can unlock their full potential, drive growth, and stay competitive in an ever-evolving market.

Have you explored the benefits of working with Microsoft Cloud Solution Providers?

If you already have one and you are only receiving services for monitoring and support, we can help accelerate your initiatives with industry experts, product development teams, AI adoption frameworks, and much more.

Contact us to learn more today!

In today’s rapidly evolving digital landscape, financial services organizations are increasingly relying on cutting-edge technologies to stay competitive and deliver exceptional services to their clients. Microsoft’s Azure Integration Services, a suite of tools designed to seamlessly connect applications, data, and processes, is emerging as a game-changer for the financial services industry.

This blog post delves into the myriad benefits of Azure Integration Services and highlights high-impact examples that demonstrate its transformative potential for financial services organizations.

The Benefits of Azure Integration Services

Enhanced Connectivity and Interoperability

Azure Integration Services offer a robust framework for connecting disparate systems, enabling financial organizations to integrate on-premises, cloud-based, and third-party applications seamlessly. This connectivity enhances interoperability, allowing for streamlined operations and improved data flow across various platforms.  Additionally, Azure offers best-in-class capabilities to support hybrid scenarios with stringent requirements for private networking & threat detection – all of which are critical in today’s cloud world.

Scalability and Flexibility

Financial organizations often face fluctuating demands and need a flexible infrastructure that can scale accordingly. Azure Integration Services provide the scalability required to handle varying workloads, ensuring businesses adapt quickly to changing market conditions without compromising performance.

Improved Security and Compliance

With stringent regulatory requirements in the financial sector, security and compliance are paramount. Azure Integration Services leverage Azure’s robust security features (including multi-factor authentication, encryption, role-based access control, and private networking) to ensure that data is protected and compliance standards are met.

Cost Efficiency

Financial organizations can reduce IT overhead costs by integrating existing systems and leveraging cloud-based services. Azure Integration Services minimize the need for extensive physical hardware and maintenance, resulting in significant cost savings.

Streamlined Business Processes

Automation is a key benefit of Azure Integration Services. By automating repetitive tasks and processes, financial organizations can increase efficiency, reduce errors, and allow employees to focus on more strategic activities that add value to the business.

High-Impact Examples in the Financial Services Industry

Real-Time Fraud Detection and Prevention

Fraud detection is critical in the financial industry. Azure Integration Services can connect various data sources and use machine learning models to analyze transactions in real-time. For example, a bank can integrate its transaction processing system with Azure Machine Learning to instantly identify and flag suspicious activities, reducing fraud risk.

Customer Relationship Management (CRM) Enhancement

Financial organizations can enhance their CRM systems by integrating them with Azure Logic Apps, Azure Functions, and Azure Service Bus. With Azure, organizations can integrate just as seamlessly with Microsoft technology (such as Dynamics) as it can with non-Microsoft technology (Salesforce).  This integration allows for real-time updates and data synchronization across customer touchpoints, providing a unified view of customer interactions. As a result, financial advisors can offer more personalized services and improve customer satisfaction.

Regulatory Reporting and Compliance Automation

Compliance reporting is often a resource-intensive process. Azure Integration Services can automate data collection and reporting from multiple sources, ensuring accuracy and timeliness. For instance, an investment firm can integrate its trading platforms with Azure Logic Apps to automate the generation and submission of compliance reports to regulatory bodies.  In addition, Azure provides security & compliance dashboards to ensure the environment itself remains secure and minimizes the threat of breaches & unauthorized access.

Seamless Payment Processing

Financial organizations can offer seamless and secure payment processing services by integrating payment gateways with Azure API Management. This integration ensures that payment data is transmitted securely and efficiently, enhancing the customer experience and reducing transaction times.  API Management benefits your products & customers as much as it benefits your development teams.  Implementing API Management provides full lifecycle support for your API’s, API discovery, and a developer portal to streamline both development and operational needs.

Enhanced Risk Management

Risk management is a critical aspect of financial services. Azure Integration Services can integrate risk assessment tools with core banking systems to provide real-time insights into potential risks. For example, a lending institution can use Azure Functions to analyze borrower data and assess credit risk more accurately, leading to better-informed lending decisions.

Conclusion

Azure Integration Services offers a powerful suite of capabilities that enable financial organizations to enhance connectivity, scalability, security, and efficiency. By leveraging these services, organizations can drive innovation, improve customer experiences, and maintain a competitive edge in the market. The high-impact examples highlighted in this post demonstrate the transformative potential of Azure Integration Services in the financial services industry, making it an indispensable asset for forward-thinking organizations.

By embracing Azure Integration Services, financial institutions can navigate the complexities of the digital era with confidence and agility, positioning themselves for sustained success and growth.

Contact us to learn more!

Learn more about our Financial services capabilities with our Financial Services Lookbook

Learn more about our Azure solutions & capabilities here.

Perficient is thrilled to announce that Amarender Peddamalku has been awarded the prestigious “Most Valuable Professional” (MVP) status in Business Applications by Microsoft for the second time. This achievement is especially significant, highlighting his continued excellence and commitment to the Microsoft community.

Amarender Peddamalku serves as the Microsoft Modern Work practice lead and digital transformation leader at Perficient. With a focus on Employee Experience and Power Platform, Amarender brings over 15 years of expertise with Microsoft Technologies, having worked with every version of SharePoint since its inception. He is passionate about building high-performing teams, crafting exceptional customer experiences, and nurturing top talent. His commitment to digital transformation is evident in his ability to lead technology implementations from sales to delivery.

In June 2024, Amarender spoke at TechCon365 (Microsoft 365 conference), leading various sessions and sharing his deep knowledge and insights with attendees. He is also presenting at upcoming TechCon 365 conferences in Washington, D.C. and Dallas. His contributions continue to enhance Perficient’s presence at conferences and within the broader tech community.

He is the sole Microsoft MVP at Perficient, a distinction that elevates the company’s reputation and unlocks valuable business opportunities. This prestigious recognition is a testament to the unwavering support and commitment Perficient has shown to Amarender and all colleagues. Reflecting on his achievement, Amarender states, “I’m so honored and grateful to be recognized as a Microsoft MVP for the second time. I want to express my heartfelt thanks to Perficient, my close colleagues, and all my project teams for their unwavering support. A special shoutout to my wife and family for standing by me throughout this journey. Microsoft products and technology have shaped my career, and now it’s my turn to give back to the community. Thank you, Microsoft, for this prestigious award, and to our amazing community for your constant support. Here’s to many more years of learning, innovation, and collaboration together!”

Read more about Amarender and his achievements here.

Perficient + Microsoft

As an award-winning Microsoft Solutions Partner, we’re recognized experts for delivering strategic solutions across the Microsoft Cloud. Our 20+ years of Microsoft experience brings true business transformation – whether it’s app modernization, cloud-native development, employee experience, hybrid work, or intelligent business applications for employees.