So, DeepSeek just dropped their latest AI models, and while it’s exciting, there are some cautions to consider. Because of the US export controls around advanced hardware, DeepSeek has been operating under a set of unique constraints that have forced them to get creative in their approach. This creativity seems to have yielded real progress in reducing the amount of hardware required for training high-end models in reasonable timeframes and for inferencing off those same models. If reality bears out the claims, this could be a sea change in the monetary and environmental costs of training and hosting LLMs.

In addition to the increased efficiency, DeepSeek’s R1 model is continuing to swell the innovation curve around reasoning models. Models that follow this emerging chain of thought paradigm in their responses, providing an explanation of their thinking first and then summarizing into an answer, are providing a step change in response quality. Especially when paired with RAG and a library of tools or actions in an agentic framework, baking this emerging pattern into the models instead of including it in the prompt is a serious innovation. We’re going to see even more open-source model vendors follow OpenAI and DeepSeek in this.

Key Considerations

One of the key factors in considering the adoption of DeepSeek models will be data residency requirements for your business. For now, self-managed private hosting is the only option for maintaining full US, EU, or UK data residency with these new DeepSeek models (the most common needs for our clients). The same export restrictions limiting the hardware available to DeepSeek have also prevented OpenAI from offering their full services with comprehensive Chinese data residency. This makes DeepSeek a compelling offering for businesses needing an option within China. It’s yet to be seen if the hyperscalers or other providers will offer DeepSeek models on their platforms (Before I managed to get his published, Microsoft made a move and is offering DeepSeek-R1 in Azure AI Foundry).  The good news is that the models are highly efficient, and self-image hosting is feasible and not overly expensive for inferencing with these models. The downside is managing provisioned capacity when workloads can be uneven, which is why pay-per-token models are often the most cost efficient.

We are expecting that these new models and the reduced prices associated with them will have serious downward pressure on per-token costs for other models hosted by the hyperscalers. We’ll be paying specific attention to Microsoft as they are continuing to diversify their offerings beyond OpenAI, especially with their decision to make DeepSeek-R1 available. We also expect to see US-based firms replicate DeepSeek’s successes, especially given that Hugging Face has already started work within their Open R1 project to take the research behind DeepSeek’s announcements and make it fully open source.

What to Do Now

This is a definite leap forward and progress in the direction of what we have long said is the destination—more and smaller models targeted at specific use cases. For now, when looking at our clients, we advise a healthy dose of “wait and see.” As has been the case for the last three years, this technology is evolving rapidly, and we expect there to be further developments in the near future from other vendors. Our perpetual reminder to our clients is that security and privacy always outweigh marginal cost savings in the long run.

The comprehensive FAQ from Stratechery is a great resource for more information.

Recently, the news broke that Optimizely acquired Netspring, a warehouse-native analytics platform.

I’ll admit, I hadn’t heard of Netspring before, but after taking a closer look at their website and capabilities, it became clear why Optimizely made this strategic move.

Simplifying Omnichannel Analytics for Real Digital Impact

Netspring is not just another analytics platform. It is focused on making warehouse-native analytics accessible to organizations of all sizes. As businesses gather more data than ever before from multiple sources – CRM, ERP, commerce, marketing automation, offline/retail – managing and analyzing that data in a cohesive way is a major challenge. Netspring simplifies this by enabling businesses to conduct meaningful analytics directly from their data warehouse, eliminating data duplication and ensuring a single source of truth.

By bringing Netspring into the fold, Optimizely has future-proofed its ability to leverage big data for experimentation, personalization, and analytics reporting across the entire Optimizely One platform.

Why Optimizely Acquired Netspring

Netspring brings significant capabilities that make it a best-in-class tool for warehouse-native analytics.

With Netspring, businesses can:

• Run Product Analytics: Understand how users engage with specific products.
• Analyze Customer Journeys: Dive deep into the entire customer journey, across all touchpoints.
• Access Business Intelligence: Easily query key business metrics without needing advanced technical expertise or risking data inconsistency.

This acquisition means that data teams can now query and analyze information directly in the data warehouse, ensuring there’s no need for data duplication or exporting data to third-party platforms. This is especially valuable for large organizations that require data consistency and accuracy.

Ready to capitalize on these new features? Contact Perficient for a complimentary assessment!

The Growing Importance of Omnichannel Analytics

It’s no secret that businesses today are moving away from single analytics platforms. Instead, they are combining data from a wide range of sources to get a holistic view of their performance. It’s not uncommon to see businesses using a combination of tools like Snowflake, Google BigQuery, Salesforce, Microsoft Dynamics, Qualtrics, Google Analytics, and Adobe Analytics.
How?

These tools allow organizations to consolidate and analyze performance metrics across their entire omnichannel ecosystem. The need to clearly measure customer journeys, marketing campaigns, and sales outcomes across both online and offline channels has never been greater. This is where warehouse-native analytics, like Netspring, come into play.

Why You Need an Omnichannel Approach to Analytics & Reporting

Today’s businesses are increasingly reliant on omnichannel analytics to drive insights. Some common tools and approaches include:

• Customer Data Platforms (CDPs): These platforms collect and unify customer data from multiple sources, providing businesses with a comprehensive view of customer interactions across all touchpoints.
• Marketing Analytics Tools: These tools help companies measure the effectiveness of their marketing campaigns across digital, social, and offline channels. They ensure you have a real-time view of campaign performance, enabling better decision-making.
• ETL Tools (Extract, Transform, Load): ETL tools are critical for moving data from various systems into a data warehouse, where it can be analyzed as a single, cohesive dataset.

The combination of these tools allows businesses to pull all relevant data into a central location, giving marketing and data teams a 360-degree view of customer behavior. This not only maximizes the return on investment (ROI) of marketing efforts but also provides greater insights for decision-making.

Navigating the Challenges of Omnichannel Analytics

While access to vast amounts of data is a powerful asset, it can be overwhelming. Too much data can lead to confusion, inconsistency, and difficulties in deriving actionable insights. This is where Netspring shines – its ability to work within an organization’s existing data warehouse provides a clear, simplified way for teams to view and analyze data in one place, without needing to be data experts. By centralizing data, businesses can more easily comply with data governance policies, security standards, and privacy regulations, ensuring they meet internal and external data handling requirements.

AI’s Role in Omnichannel Analytics

Artificial intelligence (AI) plays a pivotal role in this vision. AI can help uncover trends, patterns, and customer segmentation opportunities that might otherwise go unnoticed. By understanding omnichannel analytics across websites, mobile apps, sales teams, customer service interactions, and even offline retail stores, AI offers deeper insights into customer behavior and preferences.

This level of advanced reporting enables organizations to accurately measure the impact of their marketing, sales, and product development efforts without relying on complex SQL queries or data teams. It simplifies the process, making data-driven decisions more accessible.

Additionally, we’re looking forward to learning how Optimizely plans to leverage Opal, their smart AI assistant, in conjunction with the Netspring integration. With Opal’s capabilities, there’s potential to further enhance data analysis, providing even more powerful insights across the entire Optimizely platform.

What’s Next for Netspring and Optimizely?

Right now, Netspring’s analytics and reporting capabilities are primarily available for Optimizely’s experimentation and personalization tools. However, it’s easy to envision these features expanding to include content analytics, commerce insights, and deeper customer segmentation capabilities. As these tools evolve, companies will have even more ways to leverage the power of big data.

A Very Smart Move by Optimizely

Incorporating Netspring into the Optimizely One platform is a clear signal that Optimizely is committed to building a future-proof analytics and optimization platform. With this acquisition, they are well-positioned to help companies leverage omnichannel analytics to drive business results.

At Perficient, an Optimizely Premier Platinum Partner, we’re already working with many organizations to develop these types of advanced analytics strategies. We specialize in big data analytics, data science, business intelligence, and artificial intelligence (AI), and we see firsthand the value that comprehensive data solutions provide. Netspring’s capabilities align perfectly with the needs of organizations looking to drive growth and gain deeper insights through a single source of truth.

Ready to leverage omnichannel analytics with Optimizely?

Start with a complimentary assessment to receive tailored insights from our experienced professionals.

Connect with a Perficient expert today!
Contact Us

We are thrilled to share the highlights of our very first Google meetup hosted at our company premises on 11 Aug 2024. The event was packed with insightful sessions, engaging discussions, and valuable networking opportunities. Here’s a recap of the day’s events.

The Event was organized by Google GDG Team was open to all and entries for the event registered through the GDG event page. Attendees were provided with key details such as location, time, and speaker information beforehand.

Welcome Greeting

The day began with a warm welcome from Saniya Imroze, setting a positive tone for the event. With over 200 attendees comprising students, professionals, and a Nagpur GDG Google team, the atmosphere was charged with enthusiasm and anticipation.

Virtual Google I/O Keynote

Next, we had the privilege of presenting a recorded video by Sundar Pichai, CEO of Google. He spoke about the Virtual Google I/O Keynote, highlighting the latest innovations and advancements in technology. His insights set the stage for the tech-driven discussions that followed.

Keynote from Perficient Director

Mr. Prashant Nandanwar (Directory Cloud & API) delivered an engaging session, providing an in-depth overview of our company’s expertise in Google products. He shared compelling case studies and elaborated on our strong partnership with Google. His presentation reinforced our commitment to innovation and excellence in the tech industry.

Perficient Director (Cloud & API) Mr. Prashant addressing the attendees

Prashant also introduces his Technical Team members who were specialized in their areas like AWS/GCP Cloud, API, Artificial Intelligent, UI Team to the audience present in the event.

Perficient Director – Prashant Nandanwar with his Team, along with Senior Human Resource Manager Mrs. Shweta Rawlani with her Team.

Session on Generative AI

Following the keynote, Mukta Paliwal delivered an engaging session on Generative AI and the current developments in this space. The audience was fascinated by the possibilities of AI and how it’s shaping the future of technology.

Unleashing Flutter with Gemini

Debasmita Sarkar explored the power of Flutter with Gemini. Her session was a deep dive into unleashing the potential of Flutter, and the audience left with a clear understanding of how to leverage this powerful framework in their projects.

Interactive Quiz by GDG Team hosted

One of the event’s highlights was an interactive quiz organized by the GDG team. The participants eagerly engaged in the quiz, and the winners were rewarded with delicious chocolates. The quiz added a fun and competitive edge to the day, and everyone enjoyed the spirited participation, it was conducted by Henay Lakhwani

Lunch

As the morning sessions concluded, attendees were treated to a delightful lunch, generously sponsored by the Google team. It was a great opportunity for everyone to relax, network, and discuss the exciting topics covered so far.

Exploring APIs with Postman Flows & Google Cloud Gemini

Post-lunch, Ali Mustafa and Aanchal Mishra led an insightful presentation on exploring APIs with Postman Flows and Google Cloud Gemini. Their session provided practical knowledge on utilizing these tools for efficient API management and development.

Beyond the Checkout: Unlocking Payment Success

Later in the day, Namrata More presented an enlightening session on “Beyond the Checkout: Unlocking Payment Success.” Her expertise in the field provided valuable insights into enhancing payment processes and ensuring smooth transactions.

Felicitation & Closing Keynote

The event concluded with a felicitation ceremony and a closing keynote by Saish Adlak, capturing the essence of the day and thanking the speakers, participants, and the Google Nagpur team for their contributions.

Event Highlights

The energy and excitement of the event were captured in photos, reflecting the success of our first Google meetup. Both the attendees and the Google GDG Nagpur team as well speakers were impressed by our company premises and appreciated the smooth organization of the event. Hosting this meetup for the first time was a significant milestone for us, and we’re proud of how well everything turned out.

The Google meetup was a 4-6 hour-long event filled with insightful discussions on Google Vertex, AI, and more. We’re excited about the possibilities ahead and look forward to hosting more such events in the future.

Stay tuned for more updates and check out the event photos we’ve shared below!

GDG Nagpur Team and Speakers with Mr. Prashant Nandanwar and Mrs. Shweta Rawlani

Event Attendees

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.

Google Cloud Pub/Sub is a fully managed messaging service on Google Cloud Platform, facilitating asynchronous communication between applications in real time.

Google Cloud Platform serves as the foundation for creating, enabling, and utilizing all Google Cloud services. This includes managing APIs, enabling billing, managing collaborators, and configuring permissions for Google Cloud resources.

Refer to Part 1 – Basic Concepts to get more clarity before implementing Pub/Sub.

Prerequisites for Setting up Pub/Sub on Google Cloud

• Create a Google account
• Set up a Cloud Console project

Let’s implement PUB/SUB

Step 1: Create a Project

• Navigate to the Manage Resources page in the Cloud Console.
• From the Select Organization drop-down list at the top of the page, select the organization in which you want to create a project. (This list does not appear for a free trial user)
• Click Create Project.
• Enter a project name in the New Project window and select a billing account as applicable. A project name can contain only letters, numbers, single quotes, hyphens, spaces, or exclamation points and must be between 4 and 30 characters.
• In the Location box, specify the parent organization or folder, which will act as the hierarchical parent of the new project.
• Once all details are entered, click Create.

Step 2: Create a Topic

• Go to the Pub/Sub topics page in the Cloud Console.
• Click Create Topic.

• In the Topic ID field, provide a unique topic name, for example, My_NewTopic
• Click Save.

Leave the default values for the remaining options or set them as required, and then click Create.

You see the success message: ‘A new topic and subscription have been created successfully’.

That’s it—you’ve just created a Pub/Sub topic!

Step 3: Add a Subscription

Now, create a subscription on the previously created topic

• Once a Pub/Sub topic is created, add a subscriber to this. Click: Create subscription

• Display the menu for the topic you just created and click New Subscription.
• Type a name for the subscription, such as My_NewTopic-Sub.
• Leave the delivery type as Pull.
• Select 7 Days for Message retention duration.
• Click Create

You see the success message: ‘Subscription successfully added’.

You have just created a topic called My_NewTopic and an associated default subscription, My_NewTopic-sub

Step 4: Publish a Message on the Topic

To publish a message on the topic:

• Go to the Topic details page for the topic you just created.
• Click the Messages tab near the bottom of the page, then click Publish Message.

• Enter a suitable message in the Message.
• You can Add attributes as needed, in terms of parameter -value pair, such as Job-id = 1
• Click Publish.

Now, you have successfully published the message.

You see the success message: ‘Message published’.

Step 5: Pull a message from Subscription

• In the Cloud Console, go to the Pub/Sub subscriptions page.
• Click the subscription ID.
• In the Subscription details page, click View messages.
• Click Pull.

After pulling the message, you will see the published message details on the page.

In essence, Google Cloud Pub/Sub streamlines the establishment and setup of managed message brokers, providing capabilities such as topic organization for data streams and versatile delivery options, including publish and pull methods.

Let’s do some hands-on here.

References

1. Cloud Pub/Sub
2. Cloud Pub/Sub – Console

Google Cloud Platform (GCP), offered by Google, provides a broad spectrum of cloud computing solutions. It includes modular services across computing, data storage, analytics, and machine learning, supported by a suite of management tools. GCP stands out as a leading public cloud provider, providing a flexible array of computing services ranging from data management to web and video delivery, enhanced with advanced AI and machine learning functionalities. Its offerings encompass computing, storage, networking, big data handling, machine learning, and IoT, complemented by strong cloud management, security capabilities, and developer support.

Let’s Understand Google Pub/Sub

Google Cloud Pub/Sub is a fully managed real-time messaging service that allows users to send and receive messages between independent applications.

The Basics of Google Cloud Pub/Sub

1. Key Concepts

• Topic: A named resource to which messages are sent by publishers.
• Subscription: Represents the stream of messages from a topic to a subscriber application.
• Message: A publisher first sends data to a topic and subsequently delivers it to subscribers.
• Publisher: An application that creates messages for topics.
• Subscriber: An application that receives messages from topics through subscriptions.

2. Features and Capabilities

• Scalability: Pub/Sub can handle real-time, high-volume data ingestion and delivery.
• Durability: Messages persist and are retained until they are acknowledged by subscribers.
• Reliability: Provides at least one message delivery guarantee.
• Global: Pub/Sub topics and subscriptions can be international, enabling distributed systems.

3. Use Cases

• Real-time Analytics: Streaming data for analysis, monitoring, and alerting.
• Event-driven Architectures: Building event-driven systems for decoupled services.
• Data Ingestion: Collecting and processing data from IoT devices, logs, etc.
• Integration: Integrating systems and services in a loosely coupled manner.

4. Workflow

• Publishers send messages to topics.
• Subscribers create subscriptions to topics to receive messages.
• Messages are delivered asynchronously and can be acknowledged by subscribers.
• Supports push and pull delivery modes for subscriptions.

5. Integration and APIs

• Provides client libraries and REST APIs to integrate various programming languages and platforms.
• Integration with other Google Cloud services like Cloud Functions, Dataflow, BigQuery, etc.

6. Pricing

• Charges are based on the volume of data exchanged and operations performed.
• Offers a free tier with a certain amount of data and operations included.

7. Security

• Supports IAM roles and permissions for access control.
• It also supports encryption of data both in transit and at rest.

8. Monitoring and Logging

• Provides monitoring and alerting capabilities via Stackdriver Monitoring.
• Logs are available through Stackdriver Logging for debugging and audit purposes.

Google Cloud Pub/Sub is designed to be highly available, scalable, and reliable, making it suitable for building modern, cloud-native applications that require real-time messaging capabilities.

Request-Response vs. Pub-Sub Architecture

Request-Response Architecture

The typical model for computers communicating on a network is request-response. In the request-response model, a client computer or software requests data or services, and a server computer or software responds by providing the data or service.

• In this model, a client initiates communication by requesting data or services from a server.
• The client sends a request, and the server responds with the requested data or service.
• This model is akin to a client sending an empty truck to be filled with data by the server, which then sends the truck back and loaded.
• Examples include printing a document, where the client (e.g., spreadsheet program) requests printer services from the server (print server), which then processes and completes the print job.

Publish-Subscribe Architecture

• In pub-sub architecture, a central entity called a broker (or server) manages data distribution.
• Clients can either publish data to the broker, subscribe to receive data from it, or perform both actions.
• Publishers send data to the broker only when it changes (report by exception), while subscribers automatically receive data from the broker, but only when it changes.
• The broker is a facilitator, routing data from publishers to subscribers without storing it.
• In analogy, publishers send full data trucks to the broker, which then routes them intact to subscribing clients, cloning if necessary.
• For instance, in the diagram, clients on the left publish data consumed by clients on the right, and vice versa.

Lifecycle of a Message in Pub/Sub

In Google Cloud Pub/Sub, the lifecycle of a message typically involves several stages, from publication to consumption and acknowledgment.

Assume that a single publisher client is connected to a topic, and the topic has a single subscription attached to it. So, a single subscriber is connected to the subscription as well.

Here’s the process detailing how a message traverses through Google Cloud Pub/Sub:

• A publisher application sends a message to a specified Pub/Sub topic.
• The message is stored persistently for reliability and fault tolerance.
• At the same time, Pub/Sub delivers the message to all subscribed subscriptions associated with the topic. In this instance, there is only a single subscription.
• The subscription forwards the message to the connected subscriber application(s).
• Upon processing the message, the subscriber sends an acknowledgment to Pub/Sub, confirming successful handling.
• After successfully receiving acknowledgments from at least one subscriber for each subscription, Pub/Sub automatically deletes the message from storage, thereby ensuring efficient message management and cleanup.

Google Cloud Pub/Sub is a wholly managed messaging service on Google Cloud Platform, enabling asynchronous communication between applications in real-time. It uses topics to categorize messages and subscriptions to deliver them reliably at scale. Pub/Sub supports push and pull delivery methods, integrates seamlessly with other Google Cloud services, and ensures data security through encryption. It’s ideal for applications needing scalable, reliable messaging for use cases like real-time analytics, IoT data processing, and event-driven architectures, offering robust monitoring and logging capabilities for operational visibility.

If you want to learn more, Google Cloud provides comprehensive documentation and tutorials on Google Cloud Pub/Sub.

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.

Specialization is critical for Perficient in vetting itself as a contender in the hotly-contested Fortune 2000 digital transformation consulting industry.  Without it, our clients and customers cannot be certain that the experts we engage to successfully deliver mission-critical technical solutions have the necessary skills to ensure success.  In layman’s terms, a partner specialization for Google ensures two things: not only are these experts certified in the focus area to be delivered, but they are also the team members who will be doing the work on the project.  It’s very challenging to invest in an opportunity that does not have the required skills to deliver; specialization gives our clients the confidence that we can walk as well as talk.

As of this writing, and as a Premier Partner with Google, Perficient currently holds two specializations: Data and Analytics, and Infrastructure.  If you are reading this and have needs in either area, let us know.  We will be happy to assist with local experts in your area (all over the globe).  A third specialization, and the focus of this blog post, is Application Development.  Sincere thanks and kudos to Kyle Thompson, Technical Architect and co-author of this post, for the hours of research and validation invested to prepare us for the third-party review required for our specialization effort.

Many of us get inundated with emails advertising coding shops that can deliver in record time with low cost.  While a few of these claims may be true, it’s with ease we can disregard them en masse, because anyone who has spent time in the business of application development knows that it is an investment, it takes time, and it takes expertise.  In the list and activity below, Kyle has captured the necessary elements for our specialization in Application Development.  We are confident that our work, and this validation, will successfully achieve Perficient’s third Google Partner Specialization.

1. Planning & Requirement Analysis:
   • We engage stakeholders to define project scope and goals.
   • Detailed requirements are gathered through user stories and use cases to ensure all client needs are addressed from the start.
2. System Design & Architecture:
   • Solutions are architected leveraging GCP’s scalable and secure infrastructure.
   • Detailed design documents outline the system architecture, ensuring a clear blueprint for development.
3. Development & Coding:
   • Applications are developed using GCP services, following coding standards and best practices.
   • Code versioning and peer review processes are employed to maintain high code quality.
4. Testing & Quality Assurance:
   • Various levels of testing (unit, integration, system, and acceptance) are conducted using GCP testing tools.
   • Automated testing frameworks ensure code quality and reliability.
5. Deployment & Integration:
   • CI/CD pipelines are implemented for automated and seamless deployment.
   • Applications are integrated with existing systems to ensure compatibility and performance.
6. Operations & Monitoring:
   • Applications are monitored using GCP’s operations suite to ensure optimal performance.
   • Logging and performance metrics help identify and resolve issues proactively.
7. Evaluation & Feedback:
   • User feedback and performance data are collected to assess the application’s impact.
   • Iterative improvements are planned based on evaluation.
8. Maintenance & Updates:
   • Ongoing maintenance addresses any operational issues.
   • Regular updates and new features are rolled out to keep applications current with GCP advancements

It was fantastic discussing solutions and opportunities around GenAI with many of you at Google NEXT last month.  The landscape of business transformation has leveled up, and it’s incumbent upon all of us to be conscientious of the value of these amazing new products, while tempering our expectations of the outcomes as we explore these new solutions.  I’ll repeat the sentiment from part one of this series, in that, similar to data, the quality of our inputs determines the quality of our outputs.

Although not specifically about multi-modal Gen AI, this brief second entry will focus on the recent improvements around Gemini, namely, that Gemini Flash will soon be generally available.  Announced at the recently held Google I/O developer conference, Google’s flagship AI that powers the Vertex AI framework, Gemini, now comes in two consumable flavors.  Gemini Pro remains the go-to for deep analysis of enterprise insights.  Gemini Flash, produced to be 1) more economical (as of this writing, pricing is not yet published, but the goal is to be lower TCO than Pro) and 2) relatively reduced latency, or the time it takes for Gemini Flash to produce a response, when compared to Pro.  The proof of value for Flash is that it can be applied to repeatably consumable functions (answering customer questions specific to a company’s knowledge base, for example) and pass through this functionality to public demand.  As for latency, the more complex the prompt and data sources, the more tokens consumed by each product; therefore, the latency gap between Flash and Pro will likely increase.

I’ve fed part one of this series into the Document Summarization model in Vertex.

You are a very professional blog summarization specialist. Given a blog link, your task is to strictly follow the user’s instructions.

https://blogs.perficient.com/2024/03/21/optimize-multimodal-ai-part-1/

Please summarize the blog post linked above.

Curious to see if it will work, I changed the default prompt from evaluating a pdf to that of evaluating a hyperlink, and, true to form, Gemini admirably consumed the altered media source.  Without changing any default settings, I ran the same prompt against Flash and Pro, as seen in the screenshots below:

The blog post, “Optimize Multimodal AI: Part 1,” discusses the importance of optimizing multimodal AI models for effective results. It argues that while multimodal AI models hold great promise, they are complex and require careful optimization to reach their full potential. The post outlines a five-step optimization process:

1. Data Preparation: Ensuring high-quality, clean, and relevant data for training is crucial.
2. Model Selection: Choosing the right multimodal architecture based on the specific problem and data type is essential.
3. Hyperparameter Tuning: Experimenting with different hyperparameter values to fine-tune the model for optimal performance.
4. Evaluation Metrics: Selecting appropriate metrics to evaluate the model’s effectiveness, considering both accuracy and other relevant factors.
5. Deployment: Preparing the model for real-world use, including efficient inference and integration with existing systems.

The blog emphasizes that this optimization process is iterative and requires a deep understanding of the specific problem, data, and available resources. It also mentions that the focus on optimization will be continued in Part 2 of the series.

You can select the model in the dropdown to the upper right.  The response was very fast, and I was pleased with the summary.  I then switched the model to Pro, and hit “Submit” once more:

This blog post delves into the world of Multimodal AI, specifically focusing on its optimization for real-world applications.

The author begins by emphasizing the power and potential of Multimodal AI, which combines different data types like text, images, and videos to make more informed decisions. They highlight its advantages over single-modal approaches, particularly in complex scenarios demanding nuanced understanding.

However, the post acknowledges that optimizing Multimodal AI presents unique challenges. Instead of diving deep into solutions, this introductory part acts as a teaser for the upcoming series. It promises to explore techniques for optimizing Multimodal AI systems in detail, hinting at topics like data preparation, model selection, and ethical considerations.

In essence, this post sets the stage for a deeper dive into the practicalities of leveraging Multimodal AI, emphasizing the need for careful optimization to unlock its full potential.

Pro took a noticeably different amount of time to respond, but not disappointingly so.  What I find striking is that the Pro response was much more nuanced.  The text had warmth and depth despite a dry topic.  Neither response from Flash nor Pro got into any specifics, but still provided good insights in the summary.  I would be pleased with this output from either model, but my personal preference is the Pro output: it simply seemed more anthropomorphic, and I’m of the opinion that a model which passes the Turing test more effectively will have greater virility and longevity.  That being said, high marks to the folks at Google for producing a more economical product offering that clearly favors rapid resolution.

Are you using document summarization within your business units or organizations?  What efficiencies or outcomes are you enjoying?  Are you measuring the return on investment of time and metered consumption?  How do you plan to expand the AI footprint to solve other areas of opportunity?  Are you building against the SDK to create repeatable work streams?

In part three we will resume prompt optimization techniques and see if we can improve our GeoGuessr accuracy in more zero-shot attempts.  If you’d like to have a conversation about the thoughtful application of Gemini within your company, please reach out.  We love talking about this amazing product, and strategies to leverage it to increase profitability and market differentiation for our friends and customers.

In the realm of data management and analytics, the terms ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) have been commonplace for decades. They describe the processes involved in moving data from one system to another, transforming it as needed along the way. However, with the advent of technologies like Salesforce Data Cloud, a new concept is gaining traction: “noETL / noELT.” But what does this mean for you, especially if you’re not knee-deep in the technical jargon of data integration? Let’s explore.

Understanding ETL and ELT

First, a quick refresher on ETL and ELT:

• ETL (Extract, Transform, Load): This traditional approach involves extracting data from various sources, transforming it into a usable format, and then loading it into a target system, often a data warehouse or analytics platform.
• ELT (Extract, Load, Transform): ELT reverses the transformation step, loading raw data directly into the target system and then transforming it as needed within that system.

Both ETL and ELT have their pros and cons, but they can be complex and time-consuming processes, requiring specialized skills and infrastructure.

Enter noETL / noELT

Now, let’s talk about noETL / noELT, as championed by platforms like Salesforce Data Cloud. The “no” in noETL / noELT signifies a departure from the traditional data integration approaches. Here’s what it means for you:

1. Faster Time to Insights

• With noETL / noELT, data can be accessed and utilized more quickly. Instead of waiting for data to go through multiple transformation stages, you can start analyzing it almost immediately.

2. Real-Time or Near Real-Time Analytics

• By eliminating the upfront transformation step, noETL / noELT enables real-time or near real-time analytics. This means you can make decisions based on the most current data available.

3. Simplified Data Integration

• For end-users, noETL / noELT translates to simplified data integration. You don’t need to worry about intricate data pipelines or complex transformation logic. Data becomes more accessible and usable.

4. Scalability and Cost Efficiency

• Scalability is often improved with noETL / noELT, as it reduces the overhead associated with managing large-scale data integration processes. This can result in cost savings as well.

What it Means for You

If you’re a business user, analyst, or decision-maker leveraging Salesforce Data Cloud or similar technologies, here’s what noETL / noELT means for you:

• Ease of Use: You can focus more on extracting value from data rather than managing its integration.
• Quicker Insights: Rapid access to data means quicker insights, enabling faster and more informed decision-making.
• Adaptability: NoETL / noELT architectures are often more adaptable to changing data sources and analytical needs.

Where are we today?

As of April 2024 there are two platforms that are Generally Available (GA) that can be used like this with Salesforce Data Cloud.

1. Snowflake
2. Google BigQuery

There are two other platforms that are in Pilot mode as of April 2024.  We are excited to see those move from Pilot to GA.

1. Databricks
2. Amazon RedShift

And looking forward, as mentioned in this article at cio.com, Salesforce Data Cloud is looking towards leveraging these two abilities moving forward.

1. Allowing for data lakes that use Apache Iceberg to surface in Data Cloud with direct file access at the storage level.
2. Salesforce Data Cloud will also add zero-copy support to the Data Kits that ISVs use to distribute datasets and enrich customers’ data in Salesforce Data Cloud.

What we are so excited about at Perficient is that we can bring expertise to both sides of a project involving these technologies.  We have two different business units that focus on each side…

1. A Salesforce Business Unit with experts in Salesforce Data Cloud
2. A Data Solutions Business Unit to help with the Data Lake solutions like Snowflake, Google BigQuery, Databricks and Amazon Redshift.
   1. Here is a recent blog post from a colleague of mine in that Data Solutions business unit.

In conclusion, the rise of noETL / noELT represents a significant shift in how we approach data integration and analytics. It promises to democratize data access and streamline processes for users across organizations. As these technologies continue to evolve, staying informed about their implications will be crucial for maximizing their benefits. Embrace the simplicity and agility that noETL / noELT brings, and harness the power of data more effectively in your day-to-day operations.

Imagine a world where we can skip Extract and Load, just do our data Transformations connecting directly to sources no matter what data platform you use?

Salesforce has taken significant steps over the last 2 years with Data Cloud to streamline how you get data in and out of their platform and we’re excited to see other vendors follow their lead. They’ve gone to the next level today by announcing their more comprehensive Zero Copy Partner Network.

By using industry standards, like Apache Iceberg, as the base layer, it means it’s easy for ALL data ecosystems to interoperate with Salesforce. We can finally make progress in achieving the dream of every master data manager, a world where the golden record can be constructed from the actual source of truth directly, without needing to rely on copies.

This is also a massive step forward for our clients as they mature into real DataOps and continue beyond to full site reliability engineering operational patterns for their data estates. Fewer copies of data mean increased pipeline reliability, data trustability, and data velocity.

This new model is especially important for our clients when they choose a heterogeneous ecosystem combining tools from many partners (maybe using Adobe for DXP and marking automation, and Salesforce for sales and service) they struggle to build consistent predictive models that can power them all—their customers end up getting different personalization from different channels. When we can bring all the data together in the Lakehouse faster and simpler, it makes it possible to build one model that can be consumed by all platforms. This efficiency is critical to the practicality of adopting AI at scale.

Perficient is unique in our depth and history with Data + Intelligence, and our diversity of partners. Salesforce’s “better together” approach is aligned precisely with our normal way of working. If you use Snowflake, RedShift, Synapse, Databricks, or Big Query, we have the right experience to help you make better decisions faster with Salesforce Data Cloud.

Empowering Automation in the Digital Era

In this highly digitally connected world, companies are always looking for new and creative ways to improve efficiency, simplify procedures, and provide better customer service. Robotic Process Automation (RPA) has become a game-changing technology that helps businesses accelerate up operations, cut down on human error, and automate repetitive activities. One of the leading RPA platforms, Blue Prism, provides an extensive set of tools and features to automate Various business processes. A good example of this is the online-based Extension, a potent element that allows online applications the ability to be automated, providing up new avenues of opportunities for businesses.

Utilizing the Web-Based Extension for Blue Prism

The main objective of Blue Prism’s Web-based Extension is to enable seamless interaction between web-based apps and Blue Prism robots. With the help of this extension, robots can communicate with websites in the same manner as people do—they can provide data, extract information, and initiate activities. By leveraging this capability, businesses can automate complex processes that require interaction with web interfaces, boosting operational accuracy and efficiency. It acts as a link between the web browsers and the Blue Prism platform, enabling robots to communicate with web content, retrieve data, and take actions within web applications in the same manner as human beings do.

Key Features and Capabilities

Using Blue Prism browser extensions, Blue Prism offers native support for automating websites and apps in Google Chrome, Mozilla Firefox, and Microsoft Edge, a Chromium-based web browser. Blue Prism can interact with websites and apps that appear in these browsers because of to the extensions, which makes it simple to model business processes that depend on these websites and apps.

The Blue Prism extensions create a connection between Blue Prism and the web page in Chrome, Edge, and Firefox. This connection enables data interchange and element manipulation.

Type of Extensions in Blue Prism:

• Chrome: Used to automate websites and apps in Edge and Chrome versions that are based on Chromium.
• Firefox: Used to automate Firefox web sites and applications.

Chrome Extension for Blue Prism

Created with the goal to simplify online automation simpler within the Google Chrome browser environment, the Blue Prism Chrome Extension—also commonly known as the Blue Prism Browser—is an insignificant extension. It offers a simplified user interface for Chrome users to interact with web elements and automated tasks.

Important Characteristics:

• Integration with Chrome: This extension works in combination with the Google Chrome web browser to take advantage of its features and offer an automated task environment that is comfortable and recognizable.
• Point-and-Click Interface: By enabling users to interact with site items directly from the Chrome browser window, a point-and-click interface makes task automation simpler.
• Lightweight and User-Friendly: Users with various levels of technical proficiency can utilize the Chrome Extension because it is both lightweight and user-friendly.
• Basic Automation Capabilities: It provides basic automation features like data entry, form filling, and element selection on web sites.

Firefox Extension for Blue Prism

The objective of the Blue Prism Firefox Extension is to provide web automation in the Mozilla Firefox browser environment. It is a browser extension. This Firefox plugin lets users interact with web elements and automate tasks right within Firefox, much like the Chrome extension does.

Important Characteristics:

• Efficient Integration with Firefox: By leveraging Firefox’s features and offering a comfortable environment for online automation activities, the extension smoothly integrates with the Mozilla Firefox browser.
• Point-and-Click Interface: This function allows users to automate operations by allowing them to interact with web items directly within the Firefox browser window utilizing a point-and-click interface. Blue Prism’s cross-browser compatibility is ensured via its support for Firefox, which enables users to automate tasks in both Chrome and Firefox settings.
• Key Automation Features: such the Chrome Extension, this addon provides key automation features such element selection, data entry, and form completion on websites.

Benefits and Use Cases

• Web-Based Form Filling and Data Entry

Robots can automate data input operations which include submitting requests, filling up online forms, and updating data in web-based apps because of to the Web-based Extension. This function accelerates up data processing cycles, reduces manual error rates, and streamlines company processes.

• Data extraction and web scraping

Organizations may deploy the extension to monitor market trends, acquire competitive intelligence, generate data from websites, and add pertinent information to databases. This enhances strategic initiatives, enhances the organization insights, and makes more straightforward to make well-informed decisions.

• Automation in E-commerce

Web-based extensions can automate a wide range of operations within the e-commerce industry, including inventory management, order processing, and customer service. Businesses can improve order accuracy, maximize customer satisfaction, and optimize operational efficiency by automating repetitive processes.

• Automation in Customer Service

Robots that have been outfitted with the Web-based Extension have the capacity to automate customer service processes through their interactions with web-based chatbots, account information retrieval, and service request processing. The result makes it possible for businesses to provide individualized customer experiences, speed up response times, and increase client retention.

• Automation in Financial Services

The extension can automate operations in the financial services sector, including compliance reporting, transaction monitoring, and account reconciliation. Financial institutions can minimize operational risks, guarantee regulatory compliance, as well as enhance audit trails by automating repetitive processes.

Conclusion

Blue Prism’s Web-based Extension empowers organizations to extend automation capabilities to web-based applications enabling efficient and scalable process automation across a range of sectors and business operations. Organizations in the digital age may accomplish unprecedented levels of productivity, agility, and innovation by utilizing this feature to its full potential and following the suggested processes.

To sum up, Blue Prism’s Web-based Extension is an essential component of its goal to promote automation excellence and enable organizations to achieve success in an extremely competitive marketplace.