Accelerating Operational Reporting and Analytics for Oracle E-Business Suite (EBS)A new way to maximize your EBS investment, with no data modeling and no ETL required.

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Oracle E-Business Suite (EBS) delivers incredible value to businesses. What Oracle EBS does not offer, however, is a high-performance, quick-to-implement, low-maintenance analytics solution that easily combines data from multiple sources. As a result, many EBS customers begrudgingly resort to using multiple tools and high-cost experts to generate even the most basic reports, most commonly anchored in OBIEE.

But business leaders’ demands for faster, easier, and near-real-time reporting and analytics have dramatically increased as the business world transformed over the past decade, placing tremendous pressure on IT leaders.

These leaders feel handicapped when trying to make real-time competitive decisions and course corrections using outdated data from the hodge-podge reports available to them—they feel like they’re trying to safely fly a jet plane using a speedometer and altimeter showing them data from an hour or a day ago.

But it doesn’t have to be this way anymore. With Incorta, all Oracle EBS customers have a new, better option for analyzing and understanding their data—with no data modeling and no ETL. Incorta empowers users to make better, faster decisions by readily accessing up-to-date data and building the high-performance reports they need, all through self-service.

Most large enterprises with Oracle EBS deployed use it to power enterprise resource planning (ERP), customer relationship management (CRM), and/or human capital management (HCM) applications. Since EBS’s own reporting and analytics capabilities haven’t proven to meet the needs of most businesses, technical leads at these organizations typically relied upon three primary strategies to try to bridge the gap—strategies that now have outlived their usefulness:

• Use legacy reporting tools built on Oracle Business Intelligence Enterprise Edition (OBIEE). As Oracle EBS customers mature along their applications and analytics journey, their requirements grew from just operational reporting to now needing enterprise analytics spanning cross-functional and cross-entity reporting needs. As a result, they now seek an end-to-end enterprise analytics solution.

• Pair lightweight solutions like Noetix with Oracle BI Applications (OBIA). Companies that identified a need for operational reporting but suffered from stalled OBIA implementations, have been making do with lightweight solutions, such as Noetix. These workarounds don’t suffice anymore, but leaders are leery about investing yet again in a large, traditional, data warehouse project: they need to quickly implement effective operational reporting without investing in significant capital expenditures (CapEx).

Executive Summary

How Companies Traditionally Met Operational Reporting and Analytics Needs for Oracle EBS Data

3Accelerating Operational Reporting and Analytics for Oracle E-Business Suite (EBS)

• Build custom Informatica ETL processes upon Oracle BI Applications (OBIA). As Oracle EBS customers and early adopters of OBIA extended their applications to meet business needs, they built many custom Informatica ETL processes to support analytic requirements. But now, in order to enhance their technology stack and deal with the de-supporting of Informatica tools, they face the unappealing task of undertaking a fresh install of OBIA with Oracle Data Integration—meaning they will have to rebuild, retest, and re-deploy all of their custom INFA maps, as well as port all historical snapshots to the new implementation.

Evolving Beyond Reporting: The Need and Challenges for Enterprise-wide Analytics

As Oracle EBS deployments matured, customers realized they needed more than basic reporting. So they evaluated build-versus-buy approaches for enterprise analytics and realized buying an off-the-shelf, pre-packaged analytics application provided faster time to value than building custom data marts.

That’s why OBIA has been the preferred data warehouse-based enterprise analytics solution-of-choice for Oracle EBS customers for the last decade. But OBIA requires a vast amount of configuration and customization, and causes a lot of pain to business users.

• Data modeling and ETL changes cause months of delays due to ongoing business requests and scarce production availability, and often require extensive work to stitch together fragmented reports.

• OBIA doesn’t provide near real-time insight because ETL jobs generally require 4-12 hours to run.

• Generating meaningful reports takes hours each day, with reports already stale by the time the business user receives them.

• The growing number of cloud-based applications used by enterprises means more data is stored outside of EBS, so organizations now need to quickly integrate and analyze data from EBS and other applications.

As a result, most enterprises now are in a state of flux: despite the rapid adoption of cloud applications and the acknowledgement that legacy, on-premise applications can’t meet their needs anymore, enterprises can’t ditch most legacy applications overnight. Most will endure in a hybrid environment of both cloud and on-premise applications for the foreseeable future, grappling with these less-than- ideal options for delivering operational analytics:

• Enhance existing, on-premises data marts to support ongoing changes to on-premises data sources while bringing on-premises the source data from cloud-based applications. To do this, organizations need to continue building additional ETL/ELT maps using legacy data integration tools—adding more complexity to an already-overburdened data platform.

• Build an entirely new data pipeline on top of a modern, cloud-based data warehouse platform. These modern, cloud-based data warehouses provide separation of compute and storage, and unparalleled elasticity in the cloud. But migrating to a cloud-based data warehouse is labor-intensive and time consuming, and moving data is only the beginning of cloud-based data warehousing: you must migrate schema, data, metadata, ETL processing, users, and applications, and then continue to live with most or all of the same pain associated with traditional data warehouses. Most importantly, cloud-based data warehouses are still based on the outdated premise that enterprise analytics requires reshaping data into a star schema in the data warehouse and a data modeling framework that converts normalized (3NF) source data into flattened, de-normalized models with minimal joins using data integration (ETL/ELT) tools.

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Today’s requirements for operational reporting on EBS data are clear—and they’re usually challenging to achieve for most EBS-powered organizations.

• Support analytics for mixed-mode, multi-source analytics. A modern enterprise has both on-premise and cloud based applications from multiple application vendors. This requires a unified, conformed data model for enterprise reporting across these source applications.

• Empower business users via easy access and secure data sets. Enable self-service analysis, so business users can find their own answers to complex business questions, in only seconds.

• Enable a more scalable and robust analytics architecture. Aggregate massive amounts of complex data in real-time—without using a data warehouse or reshaping data into analytical formats.

The Breakthrough Solution: Business Intelligence Reimagined

No Data Modeling. No ETL.

To break through the constraints of traditional BI, you have to approach the problem in a fundamentally different way. What if you could skip the data modeling and ETL process altogether, and use thousands of joins against data in its source form, with all details and data securely intact?

Incorta does just that by bringing together three important database technology developments in an exciting new way—and by doing so, challenges the conventional, mistaken belief that star schemas need to be part of the foundation of modern enterprise platforms.

1. Incorta’s Direct Data Mapping™ platform enables you to query large, complex datasets with sub-second query response time.

2. Incorta loads full copies of all application data into its data store without needing data modeling, flattening or ETL. It provides full data fidelity by capturing data at the most granular level and allows you to drill into details from summarized reports.

3. Incorta allows you to leverage your existing infrastructure (on-premises or in the cloud) without needing specialized hardware and while still enjoying enterprise-grade capabilities, such as high availability and disaster recovery.

Incorta Direct Data Mapping

At the heart of Incorta’s breakthrough solution is its Direct Data Mapping engine. Its ability to scale analytics for large and complex data sets eliminates the need for data modeling, unnecessary parts of ETL, and pre-aggregations. Instead, Incorta dynamically ingests data from multiple sources in real time. And, because it can analyze in sub-seconds large data sets that require hundreds of joins, it doesn’t force users to design star schemas or flatten data sets.

Incorta Direct Data Mapping lets IT ingest source application schemas in their entirety, without needing the parts of ETL that ingest only subsets of the source. With the entire data set already inside Incorta, business users can feed their data curiosity with self-service analytics.

A New Approach to Operational Reporting for EBS Data: Analytics on a Scalable, Modern Platform

SQL

BI Tools

Incorta Visualization Suite

EDW & Databases

Big Data

Applications

Incorta Analytics Platform

Python Analytics Engine

DataLoader

Parquet + [Data Map] Shared/Unlimited Storage

Cloud, Hybrid, On-PremisesExcelExcel

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Incorta’s modern enterprise analytics platform with no star schemas required.

Incorta Gives Organizations:

Accelerated time to value. Deploy in days or weeks, not months. Generate new reports in minutes or hours, not weeks or months.

1 Self-service reporting and analytics. Make better decisions faster with the availability of source-level data granularity, combined with all relevant history; plus, cross-functional and role-based analytics.

2 Top-line to transaction data access. Drill from top-line analysis down to transactions without any concern of data inaccuracies because pre-aggregations and summarizations no longer are necessary.

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Incorta means no reshaping of data and no need for additional data integration platforms.

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Incorta’s Data Enrichment

With Incorta, you can enrich data without having to transform it. While Incorta does not reshape data into a dimension model, it still provides a rich set of capabilities to enrich enterprise data: it simply supports the capabilities of a traditional dimensional data model in an easier and more elegant fashion.

That’s because, on top of Incorta’s Direct Data Mapping—which eliminates the need for schema development and ETL—Incorta’s native, built-in support for PySpark makes it easy to support powerful data enrichments without needing another data integration tool.

For example:

• Snapshots – Creating a snapshot of “point-in-time” data. A snapshot table holds the same transactional data as its source system, with additional fields for tracking the date of extract. A collection of these snapshots with a fixed cadence like daily, weekly, monthly helps with rear-view trend analysis. For example, weekly and monthly trends for inventory. Or, Accounts Receivables aging by month.

• Slowly changing dimensions – Preserving historical data by creating two or more records for a natural key of the dimension.. in the example above, rear-view analysis might require the employee location to be as of a certain date in the past. By supporting Type 2 slowly changing dimensions, Incorta can retain the full history of values, when the values of a chosen dimension attribute changes in the source system. A good example of this scenario is when an employee location changes every time he or she is transferred.

• Role-playing dimensions – A single dimension like Date or User can be used in an analysis and plays a different role, based on the join to a transaction fact. For example, there could be multiple dates for sales orders (sales booking date, sales quote date, sales fulfillment date, etc.). In this case, Incorta supports creating aliases of the same Date dimension, so the same Date dimension and its rich set of attributes can be used to analyze sales revenue by booking date as well as fulfillment date.

• Handling data and object security – Data governance is a critical requirement to support enterprise analytics. In many cases, the security model has to be rebuilt in an enterprise data mart. Incorta can leverage source objects to help define row-level data security by organization, business unit, department, etc. Similar logic can be applied to provide secured access to objects like dashboards, and to logical and physical schemas.

• Advanced analytics – Incorta enables you to build advanced analytics, such as predicting Accounts Receivable defaults, inventory stock outs etc. Incorta makes this possible by leveraging pySpark and its machine learning frameworks.

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Incorta’s Pre-Built Analytic Applications

Incorta provides a range of pre-built analytic applications for Oracle EBS, with pre-built content that’s both broad and deep, and spanning several functional areas. These pre-built applications expedite an organization’s migration from legacy reporting tools and drastically speed time to value, giving users immediate access to logically grouped content areas and several sample dashboards by persona to help answer their critical business questions.

Broad coverage of pre-built content accelerates operational reporting and analytics on the Incorta platform.

A sample set of pre-built, persona-based Incorta dashboards across several functional areas.

Incorta: A Flexible Tool for Any EBS Environment

• Deploy operational reporting on top of on-premises Oracle EBS or cloud-based data stores

• Replace an existing data warehouse solution

• Augment an existing data warehouse and use Incorta to build future reporting and analytical applications (including self-service apps)

• Build reporting and analytical apps in Incorta, using other external analytic tools like Tableau, Power BI, Microstrategy, etc., for visualization

• Use Incorta as a data management layer between an enterprise data lake and self-service analytic tools

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Incorta in Action: Real-World ExamplesIncorta has been deployed in some of the largest and most complex enterprises in the world, delivering to them in just weeks or even days monumental impact based upon their enterprise application data. For example:

Shutterfly faced an eight-figure stockout problem.

Online image publisher Shutterfly is one Oracle EBS customer that faced monumental inventory reporting challenges. For Shutterfly, stockouts were an eight-figure problem that rose to the board level. Operating leaders knew they had a stockout problem and knew the enterprise had the data to solve it, but the limitations of Oracle’s EBS tools made it impossible to put the right data into the hands of the people that needed it. Shutterfly buyers and planners spent hours each day running reports on data from EBS, then combining them together, in a futile attempt to gain up-to-date insight into their inventory. This hodge-podge reporting mix of Excel spreadsheets and Oracle tools was inefficient and unreliable, and made it almost impossible to access key data points stored in Oracle EBS, such as those related to stock outs and excess and obsolete (E&O) inventory.

With Incorta, Shutterfly generated full payback in one quarter and reduced stockouts by more than 90%!With a goal of reducing stockouts by 50 percent, Shutterfly deployed five Incorta-powered, customized analytical applications in just six weeks to help managers optimize inventory and understand data in real time. The plan was to reduce inventory-related issues and expenses by better accessing and understanding key supply chain data stored in Oracle EBS. Shutterfly generated full payback in only one quarter and reduced stockouts by over 90 percent—substantially exceeding their goal! User-driven, self-service analysis solved inventory issues at the busiest time of year, and empowered users to now build dashboards and gain new insights at any time without any help from IT.

Broadcom wanted self-service operating analytics.

At Broadcom, enterprise data complexity and a bogged-down, traditional BI stack led to headaches. it It typically took three to four months to deploy a new business report that integrated data from Oracle with data from other enterprise applications, but the executive team wanted self-service reporting in Excel in order to improve their strategic decision-making and business agility.

With Incorta, what used to take 8 to 12 weeks to build now requires only seconds!Broadcom deployed Incorta to enable self-service access to analytics. Today, Broadcom’s CEO and more than 300 other users have instant, self-service access to operating analytics in Excel, with intact source-level data fidelity and security. They can generate new analytical applications in days instead of months, and provide business users with quick access to information following acquisitions. In addition, the new, lightweight tech stacks translate into less time and fewer people required to maintain and manage the systems.

Inaccessible Oracle EBS data jeopardized Keysight business operations.

The recognized leader in electronic test and measurement equipment innovation for 75 years knew its outdated reporting strategy was costing its business time and money. Keysight leaders couldn’t make timely, data-informed decisions; easily modify existing reports; or quickly integrate critical data from M&A activities. And IT teams needed to re-capture and re-deploy their valuable time while phasing out inadequate reporting technologies.

Keysight achieves one-second response times on queries run against 700 million records and 40 tables!With Incorta, Keysight reduced M&A integration timelines from 12 months to a few weeks, and now delivers revenue reports that run or refresh in only one minute (versus the 6+ hours required before). Users can do aggregation and detailed analysis in the same report, and add new fields to a report or dashboard as needed, instead of waiting for quarterly refreshes. In addition, eliminating performance tuning and database maintenance freed up 13 technical resources.

About Incorta

Incorta’s enterprise analytics platform aggregates complex business data in real-time, bypassing the need for a traditional data warehouse. Powered by the industry’s first Direct Data MappingTM engine, Incorta provides unprecedented query performance and eliminates costly join operations altogether. Incorta reduces from months to days the time required to roll out new analytics applications, and reduces query and reporting times from hours to seconds. Backed by GV (formerly Google Ventures), Incorta is deployed in the Fortune 10 and powers analytics for some of the world’s largest and fastest-growing companies.

To learn the fastest way to what matters, visit www.incorta.com or join the conversation on Twitter @incorta.

With tens of thousands of tables, hundreds of functional modules, and often thousands of concurrent users, Oracle EBS tests its customers’ IT infrastructure limits. Incorta’s modern data analytics platform addresses the complexities in legacy data warehousing constructs to give EBS customers the analytics and reporting they’ve waited for. With Incorta, EBS users can make better, faster decisions by readily accessing up-to-date data and building the high-performance reports they need, all on their own.

For more information, please watch the webinar Keysight: Operational Analytics without Cumbersome ETL or Star Schemas

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