Oracle Cloud provides several big data services and deployment models. The big data service choices enable you to start at the cost and capability level suitable to your use case and gives you the flexibility to adapt your choices as your requirements change over time. Big Data Cloud Service and Big Data SQL Cloud Service enable an end-to-end offering combining Oracle’s rich analytics platform with the leading Hadoop distribution in a seamless, integrated, secure Data Lake. Oracle uniquely offers these services in Public Cloud.

There are several steps involved in successfully provisioning Oracle Big Data Cloud Service. At Collaborate 19, I will go into the high level details of provisioning an Oracle Big Data Cloud Service instance and talk about how to take advantage of analytics.

Collaborate 19 Session: Oracle Big Data in the Cloud

Sunday, April 7

3:00 – 4:00 PM

CC 2ND FL 217A

Raghuraman Syama, Senior Technical Architect, Oracle Business Intelligence

Click here to add the session to your schedule.

This year, Collaborate 19, is being held April 7-11 in San Antonio, TX. Make sure to connect with Perficient at booth #937 and meet with subject matter experts and thought leaders and learn how we’ve leveraged our extensive expertise in ERP, EPM, and Business Intelligence to drive digital transformation for our customers.

We’re pleased to have been selected to present on key topics from Oracle Business Intelligence and Oracle EPM to ERP. Join us for any of our eight sessions at Collaborate!

Learn more about all of the sessions here.

Oracle Autonomous Analytics Cloud BI Admin Tool is similar to the BI Admin tool. You can download the tool from the following link:

https://www.oracle.com/technetwork/middleware/oac/downloads/oac-tools-4392272.html

When you try to establish the connection to Essbase Cube for import using this tool, you might get the following error:

Essbase Error 1040048: HTTP communication failed with error [Failed to perform curl request with error [Peer certificate cannot be authenticated with given CA certificates] to the following address

Solution:

In order to resolve this error, you need to download the cacerts.pem and copy it to the AdminTool Essbase folder on your machine. Refer to Doc ID 2454121.1 at support.oracle.com for the detailed steps related to this issue along with the cacerts.pem download.

Oracle Internet of Things (IoT) Cloud Service helps you make critical business decisions and develop strategies by providing numerous applications that allow its users an inside perspective on their company’s facts and figures.

Some of these applications include connecting your devices to the cloud and analyzing data and alert messages from those devices in real time. Additionally, through IoT Cloud Service you are able to integrate your data with enterprise applications, web services, or with other Oracle Cloud Services, such as Oracle Business Intelligence Cloud Service.

While the IoT Cloud Service infrastructure provides the analytics to help a business succeed, many are still unfamiliar with this application and the analytics it provides.

For that reason, I encourage you to join me Thursday, July 12, 2018 from 11:00 AM – 12:00 PM CDT for my “Introduction to Analytics in Oracle Internet of Things (IoT) Cloud Service” webinar. In this session, I will give a brief walk through of analytics in Oracle IoT. Be sure to visit this page on the ODTUG website to register to be part of this informative session.

More Perficient Sessions on ODTUG to come!

On August 7, my colleague Mazen Manasseh will be presenting on the Road to Oracle Cloud from OBIEE and BI Apps. Be sure to tune into that webinar early next month to learn more about the various components of OBIEE and OBIA and the best practices.

Additionally, my colleague Nandini Nehru will be presenting a “Case Study” webinar on August 14 covering the Implementation of a One-of-a-Kind Driver-Based Rolling Forecast Model at MD Anderson Cancer Center Using Hyperion Planning with ASO. Be sure to tune into that interesting session as well.

Applies to Oracle Analytics Cloud Service – version 17.4.5 and later

To learn more about why Oracle Analytics Cloud (OAC) Backup Operation fails, run the diagnostic collection script on the OAC server. Refer to Oracle Support Document 2236000.1 (How To Collect Diagnostic Files and Logs in Oracle Analytics Cloud (OAC)).

The diagnostic collection script generates an archive file containing all the log files. When you take a look at those log files, you might see the following error.

[OBI-LCM-99999] An unknown or unexpected error occurred

If you look further into the detailed logs, you might see something similar to
INFO: Java HotSpot(TM) 64-Bit Server VM warning: INFO: os::commit_memory(0x0000000080000000, 1082130432, 0) failed; error=’Cannot allocate memory’.

You encounter this error because the system is running out of memory.

Solution

This is a known issue as per the Oracle Support Document 2381969.1 (OAC : Oracle Analytics Cloud Backup Operation fails [OBI-LCM-99999] An unknown or unexpected error occurred: Error Occurred during Export: Operation Failed), and Oracle is investigating the memory consumption issue.

You have two options now.

Option 1: Go to Cloud console and stop the OAC service. Once stopped, then start the service.
Remember: do not stop and start the service via scripts. This will not release the memory.

Option 2: Scale up the service instance.

Oracle is implementing Artificial Intelligence and Machine Learning in several of their cloud products. One of the cloud offerings is Oracle Autonomous Data Warehouse.

Oracle Autonomous Data Warehouse makes it easy to create a secure, fully managed Data Warehouse service in the Oracle cloud. You can start loading and analyzing your data immediately. It’s built around the Oracle database and comes with fully automated data warehouse specific features that deliver outstanding query performance.

Oracle Autonomous Data Warehouse is provided  as a managed cloud service running on an optimized high-end Oracle hardware systems. This means you don’t need to spend time thinking about how you should store your data, when or how to back it up, or how to tune your queries. Oracle takes care of everything for you. You can select the exact combination of storage and CPUs to fit your project and your budget. Your data is always backed up and always encrypted in Oracle’s cloud. You can  load all different types of data from worksheets, to log files, to data files stored in Oracle’s cloud-based object store, and load that data into your Autonomous Data Warehouse Cloud. It comes complete with its own web-based notebook and reporting services to help you build and share your data analysis with others.

It seamlessly integrates with all the most popular data warehouse tools, so all you need to do is connect your favorite tool and you are ready to go.

Oracle Autonomous Data Warehouse Cloud does not require database administration. It uses artificial intelligence to deliver unprecedented reliability, and you do not need to configure or manage any hardware, or install any software. Autonomous Data Warehouse Cloud handles creating the data warehouse database, backing up the database, patching and upgrading the database, and growing or shrinking the database.

Oracle Cloud is open, allowing customers to utilize the service in a true hybrid cloud model, as well as supporting the utilization of third-party applications, tools or even open-sourced Hadoop solutions. Oracle’s data warehouse cloud solution combines a fully integrated cloud, the industry’s best database, a comprehensive cloud platform and the power of choice to provide a path to the cloud that’s right for you.

Oracle Internet of Things (IoT) Cloud Service is a managed Platform as a Service (PaaS) offering that helps you make critical business decisions and strategies by allowing you to connect your devices to the cloud, analyze data and alert messages from those devices in real time, and integrate your data with enterprise applications, web services, or with other Oracle Cloud Services, such as Oracle Business Intelligence Cloud Service.

Oracle IoT securely connects all your devices to IoT cloud service, gathers valuable data from those services, analyzes and processes the data received in real-time and delivers the process data to your enterprise applications or other integrated services.

There are several steps involved in successfully provision an Oracle IoT Cloud Service.

Collaborate 2018 Session: Introduction to Analytics in Oracle Internet of Things (IoT) Cloud Service

At Collaborate 18 (April 22-26 at Mandalay Bay in Las Vegas), I will go into the details of provisioning an Oracle IoT Cloud Service instance and talk about how to do analytics using the IoT.

I invite you to attend the following Collaborate 18 session to learn more:

Introduction to Analytics in Oracle Internet of Things (IoT) Cloud Service
Wednesday, April 25 | 11:00 – 12:00 PM
BANYAN D | Raghuraman Syama, Senior Technical Architect, Business Intelligence

Can’t Attend?

If you are unable to attend, but would like to get a copy of any one of the session slides, please leave a comment, and we’ll ensure you get the slides after the show.

More Perficient Sessions

Our Perficient Oracle team is honored to have been invited to present on seven unique topics across multiple tracks at Collaborate 18. Learn more about all of the sessions here.

I recently ran into an issue related to the RPD development. The RPD was already in place and was working. The only change that was done to this RPD was that several column names were renamed to more appropriate names as per the use case in the BMM layer. After this change, the RPD passed the consistency check, and successfully deployed. But, when I try to create a report, I ran into the following errors:

[nQSError: 14077] None of the dimension tables are compatible with the query

In some cases, I got the following error as well:

[nQSError: 14025] No fact table exists at the requested level of detail:

I saw a similar errors reported in other forums related to 11g, but the majority of those talked about inconsistent modeling.

I started taking a closer look at the modeling and joins, but none of them seemed to be wrong. As a test, I deployed this RPD to a separate machine running the same OBIEE 12c. To my astonishment, the reports ran fine, and I did not see any of the errors listed above.

After this test, I was fully convinced that, it was either an environment or database issue.

Solution:
There may be more solutions, but these are the ones I found:

The first option, and a cumbersome one as well, is to create a new Business Model in the BMM and mimic each and every Dimension and Fact from the ones that were not working. Basically, just recreate the new model. Deploy the updated RPD, and the reports will work.

The second option, and the easier one, is to duplicate the Business Model with a new Subject Area from the non-working Business Model. After duplicating it, delete the non-working Business Model and the associated Subject Area. Deploy the updated RPD, and the new duplicated Subject Area should work.

I hope this will help anybody running into a similar situation. This is not the only solution for this problem, but these errors can also happen if your Business Models are not consistent.

I am sure many of you are already familiar with Serverless Computing, and might have already used it in your projects. In this blog post, I’ll share my thought process around Serverless Computing, what it is, things to know before you start using it, and where you can use it.

The credit for Serverless Computing goes to Amazon. They are the pioneers, and started the Serverless movement with the launch of AWS Lambda. Later, several cloud vendors followed the bandwagon and started their own Serverless offerings.

Does Serverless mean no servers?

It’s a misnomer to say that. Certainly there are servers involved in running your code. It’s just that you are not managing these servers. Your cloud provider manages them for you, and unlike regular cloud subscriptions like PaaS, they are not always running. Serverless provides a layer of abstraction on top of a cloud infrastructure. Developers no longer need to worry about physical or virtual servers. Instead, Serverless allows you to run code directly in the cloud without provisioning or managing servers.

How does your code get executed?

Basically, your application alerts the cloud server when it should execute an action, and when that action is complete, the server essentially stops running until another action is requested. It is often referred to as Function-as-a-Service (FaaS) or event-based architecture. Essentially, it’s an event which triggers a function. It is a piece of code which automatically starts the server which runs this code. Once complete, the server automatically stops running. To understand how exactly the Serverless code gets executed, let’s look at a popular example from Amazon which talks about the most common use case for AWS Lambda.

Let’s say you are building custom photo library web software which allows you to upload your image and displays that image equally well on all devices such as laptops, mobile phones, and tablets. In order to do this, you upload an image to S3 bucket. As soon as the image is uploaded to S3 bucket, an event can be triggered to resize the file so that it looks good on all devices, then compresses the file to save the disk space, and finally copies that image file to a processed folder. The code that does all this is AWS Lambda, which runs only when the event is triggered. Once the file is processed, the servers that power the Lambda actions will not be active.

Who Offers Serverless?

As I previously mentioned, Amazon is the main pioneer in this technology, and their Serverless offering is AWS Lambda.

• Google offers Google Cloud Functions
• Microsoft offers Azure Functions
• IBM offers IBM OpenWhisk

Apart from Amazon, Google, Microsoft, and IBM, there are several others that provide Serverless Computing, and some are open source as well.

What Are the Benefits of Serverless Computing?

There are several companies in the world who leverage Serverless to power their products. For example, Netflix implemented AWS Lambda to power their products at scale.

Some of the benefits are:

Cost:
The subscription cost for Serverless is less compared to other PaaS subscriptions. The reason is that the servers only run when necessary, and essentially during the execution period of the Serverless code. You don’t have to pay for idle server time.

Elastic:
With Serverless the functions that you run can automatically scale up to accommodate spikes in traffic, and scale down when there are fewer concurrent users without any manual management. This will help minimize costs, since you will only pay for what you use.

Administration:
Administration is automated, you do not have to update underlying software when a patch is available. There are no operating systems that you need to secure, or patch. You can simply concentrate on building the best product possible, without worrying about the infrastructure.

Microservices:
Microservices is a popular approach to development in which engineers build modular software that’s more flexible, scalable, and easier to manage than its monolithic counterparts. Serverless architecture fits very well with microservices.

What Are the Challenges?

As you all know, with every new technology the challenges and needs will start to take shape. The primary issues are with the internal implementation of the various cloud providers. Several FaaS offerings have emerged in the market, and apart from the prominent vendors, some are developed by the community. The challenges mentioned here are common to all FaaS providers, but each vendor might offer a unique solution to overcome some of the challenges.

Costs:
Though Serverless functions run only for a short period of time, sometimes it’s not possible to predict/limit the costs. Some vendors provide an alert mechanism wherein you can setup a threshold limit. Once the cost crosses the set limit, you will be notified. Still, you have to monitor frequently and take required steps to mitigate unforeseen cost increases.

Vendor Lock-in:
The main root cause for this is often not Serverless functions/FaaS functions itself, but the integrations with other vendor offered proprietary services. Once integrated with their services, it takes a while to move the code across vendors if you decide to do so, and it also takes time if the code base is quite huge.

Integration testing:
Integration testing becomes hard, and most of the time requires mocking the integrated services or running some alternate functionality for each one of them.

Service Discovery:
With distributed architecture, the service discovery is enabled for the services to be discoverable, if not externally, at least internally to each other. Though Serverless architecture is a distributed architecture, services aren’t currently discoverable, but will be in the future.

Configuration:
The best practice for most of the applications is to use environment variables to manage the configuration. Setting the configuration variables are not yet supported by most of the vendors. But, major vendors like AWS have already started supporting it.

So, considering all the benefits and drawbacks that we have with Serverless Computing, there are definitely several use cases where you can leverage Serverless functions. Most of the mobile based applications, games, voice enabled applications, IoT, media industry, and several others which are coming up/growing in the market are leveraging Serverless architecture. Considering there are several vendors and community who are trying to address some of the issues, add newer functionality… Serverless is the next big thing.

Oracle Integration Cloud Service is a PaaS offering from Oracle. Since its introduction in 2014, the Oracle Integration Cloud Service has gained its position in the Gartner Magic Quadrant.

Oracle Integration Cloud Service lets you connect to both cloud, and on-premises applications.

With Oracle Integration Cloud Service, you can connect to all of the Oracle SaaS applications that you are subscribed to and start integrating them. It is pre-loaded with your existing Oracle SaaS subscriptions. It provides native adapters for seamless integration with several applications. It provides connectivity to Oracle SaaS applications, such as Oracle Sales Cloud, Oracle RightNow Cloud, and so on. It has a huge growing library of connectors for Oracle and 3rd party applications.

Instead of creating the integration from scratch, you can simply select from a growing list of integrations built by Oracle and Oracle partners. You can also easily design integrations from scratch.

Oracle Integration Cloud Service provides a powerful and intuitive browser-based visual designer that lets you drag and drop application adapters to develop integrations. With this you can configure your adapters, model your data mapping, and activate your integrations with zero coding. With a rich monitoring dashboard, you can schedule, monitor, manage integrations, and quickly locate transactions of interest and their outcome through the rich search criteria. You can easily publish and subscribe to messages.

Oracle Integration Cloud Service provides a secure, enterprise-grade connectivity regardless of the applications you are connecting to or where they reside. It provides a highly secure environment for physical security, an operating system and virtualization layer security, and tenant isolation. It is protected by design-time and run-time security to ensure that only authorized users can access the web console at design-time or invoke Oracle Integration Cloud Service integrations at run-time.

Oracle Integration Cloud Service is built on a proven enterprise grade run-time that provides a high performance, reliable, and available platform for executing mission-critical integrations. Oracle manages all the backup, patch updates, and upgrades. When you subscribe to Oracle Integration Cloud Service, you also have the option to install an on-premises version of Oracle Integration Cloud Service in your local environment.

The main benefits are

• Faster integration of applications
• Increased business agility
• Lower cost of ownership

Want to learn more?
Talk to our Perficient BI Team to get more insight into the implementation of the Oracle Integration Cloud Service and other related Oracle Cloud offerings. Learn how we can help your company transform your data to Oracle Cloud and make the most of the scalability, innovation, and cost efficiency.

I recently ran into an issue in which I was unable to ping a guest VM from a host machine. Let me explain my scenario before jumping into how I resolved the issue.

I built a Linux VM running on Windows 7. This VM included all the Oracle BI related products such as database, DAC server, Informatica server, and several others. I installed the DAC client and Informatica client on the Windows 7 machine. I configured the VM network to NAT. This was working great without any issues. I could connect from the host to VM using either an Ethernet port or Wi–Fi.

When I tried the same image at the client’s side it did not work. I could not ping from host to VM guest. I started getting an error. The first thing that I thought of was to change the connection over to Host-only for the VM network, and the issue still was not resolved.

There are several related solutions available in the internet, but it all depends on the configuration of the machine, and the firewall rules. In my case, I updated the Kaspersky virus scan to latest version, and thought that might be blocking the connection. Later found that was not true.

Solution:
So, what did I do to resolve the issue? Here are the steps:

• • Disabled the VMware Network Adapter VMNet8

• • Changed the properties for the Internet Protocol Version 4 under VMWare Network Adapter VMNet8 to Obtain an IP address automatically

• • Removed the network from the VM
  • Enabled the VMware Network Adapter VMNet8
  • Re-added the Network to VM, and set it to NAT

• Restarted the machine

After following the above steps, it started working.

Are your business data volumes growing rapidly? Are your business data sets becoming increasingly varied and complex? Do you get data from number of sources, and in different formats? Do you want to turn your data sets into meaningful information by taking advantage of automated data preparation and processing? Then Oracle Big Data Preparation Cloud Service is the Oracle Cloud service for you.

Oracle Big Data Preparation Cloud Service is a PaaS subscription model available in Oracle Public Cloud. It is a comprehensive, and secure solution that lets you automate and streamline data ingestion and enrichment in the Oracle Cloud.

Oracle Big Data Preparation Cloud Service is available as a massively scalable service built on Hadoop/Spark, and enhanced with Natural Language Processing and Reference Dataset Knowledge Service.

Oracle Big Data Preparation Cloud Service gives you an easy-to-use way to work with your data. It provides an intuitive and interactive user experience, guiding you with a machine learning-driven recommendation engine. With its coordinated features, you can automate, streamline, guide the error-prone process of data, and you can significantly reduce the amount of time needed to ingest, prepare, standardize, and enrich data in every step without costly manual intervention.

Oracle Big Data Preparation Cloud Service rapidly automates data processing and enrichment in a fully provisioned environment. It detects duplicates in your data, based on a flexible set of criteria. It uses a vast array of reference data to analyze content without relying on metadata, and add related entities based on service recommendations.

Once you interactively create a transform script to ingest a new data set, a similar process of ingesting data sets can be automated and operationalized. You can create policies to run transformations on a regular schedule or you can use a rich set of RESTful APIs to completely automate the process.

You can track and govern all the scheduled or automated ingestion jobs via a highly visual and interactive dashboard where you can see all the activity in the service at different levels of detail giving you visibility into potential problems before they affect downstream processes such as enterprise ETL, enterprise reporting, and data recovery.

Transform the way you prepare data for analytics using Oracle Big Data Preparation Cloud Service.

Want to learn more?
Talk to our Perficient BI Team to get more insight into the Oracle Big Data Preparation Cloud Service and other related Oracle Cloud offerings. Learn how we can help your company transform your data to Oracle Cloud and make the most of the scalability, innovation and cost efficiency.

Oracle Big Data Discovery Cloud service is a single-tenant Platform as a Service (PaaS) offering in Oracle Public Cloud. It is a part of Oracle’s complete Big Data solution, available on-premises and in the Cloud for seamless Big Data management and analysis in any environment.

Oracle Big Data Discovery Cloud Service is a set of end-to-end visual analytic capabilities in the cloud that leverage the power of Oracle Big Data Cloud Service, and Apache Spark to transform raw data into business insight in minutes, without the need to learn complex products.

Oracle Big Data Discovery is a single product allowing you to quickly turn raw data in Hadoop into actionable insight. Visual interface enables anyone to find relevant data sets, explore those data sets, transform data in Hadoop, discover new insights from the data, and easily share results.

The digital age has made it faster and easier to capture, and process data. Datafication is the capture and use of information in daily activities. The problem is the world’s ability to produce data has already outstripped most organizations’ ability to use it. Computers have improved quite a bit in recent years, so you can capture much more data than you could in the past. But, can you understand and manipulate all that data? Many organizations simply discard potentially valuable data because they simply don’t have the resources to analyze it. Imagine what beneficial information is being thrown out with it.

Consider another issue, how much time do you spend on a typical business intelligence project? How much time do you spend preparing the data? How much time do you spend defining the requirements to publishing the data? Traditionally, you would first try to predict all possible business questions upfront like modeling, locating, acquiring data, and so on. Then you’d need to design a model to answer any questions, and then hunt down data sources, review them to make sure you understand them, confirm you have the right data, manipulate feeds to fit into the model, and finally publish it. For most organizations, that takes a significant amount of time and resources.

Big data projects increase the costs of data preparation significantly. This is because of the extreme increase in Volume, Variety, and Velocity of big data. Volume means a massive amount of data, much larger than organizations typically handle. Variety means, diversity of data, including text from social networks, image data, feeds from monitoring equipment, and so on. Velocity means how fast data flows into an organization.

Today the world produces and captures data faster than ever before. You’ll need significantly more time to manipulate these new, extremely large, and messy data sets before you can really understand the information within them and know what action to take to improve your business. And that generally requires highly specialized and scarce resources. Most organizations spend about 80% of their effort on data preparation in a typical BI project, and only 20% on analysis and execution. And big data only exacerbates the time and costs associated with these projects. We need to find a way to turn those numbers around so the bulk of your time is spent on analyzing data and discovering new information that helps you boost business, while also reducing the overall costs. To expedite the data preparation of big data, we need hardware and software to process data faster. We also need a tool that automates much of the data preparation, reducing dependence on technical experts with specialized skills, such as knowledge of advanced programming languages like R. Inevitably, data sets include incomplete or incorrect information, and this is amplified with big data. So we also need a tool that helps users identify any data that needs to be cleaned up. And we need a tool that empowers more users to do some of the things that traditionally could only be done by data experts with specialized skills. Like searching through many large data sets to identify the data sets needed for analysis. A tool that can quickly wade through millions of records and automatically produce visualizations that highlight trends, anomalies, and the like, so business users can immediately focus on the most important information. And finally a tool that also lets business users manipulate the data themselves during their investigation and analysis, and create their own visualizations that provide insights that they can then share with others. By empowering business users to work with big data themselves, you eliminate the bottleneck typically created when they had to wait on scarce resources to do these things for them, saving time and money. These are just some of the capabilities of Oracle Big Data Discovery.

Oracle Big Data Discovery Cloud Service gives you the power to run a full speed data discovery lab that fuels your big data portfolio with an endless pipeline of high-octane data projects. It’s the visual face of all your big data. Now you can tell what’s interesting and where to focus at a glance. Find and explore your data just like shopping online and rapidly enhance it with hundreds of pre-built transformations and powerful enrichment capabilities all at your fingertips. Then share your discoveries and rich visual galleries in easy analytic apps that show you the true value in your data, and you can easily enhance data available to your other Big Data projects in Oracle’s big data management system.

Want to learn more?
Talk to our Perficient BI Team to get more insight into the Oracle Big Data Discovery Cloud Service and other related Oracle Cloud offerings. Learn how we can help your company transform your data to Oracle Cloud and make the most of the scalability, innovation and cost efficiency.