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EDW: The Next Data Frontier

March 20, 2017 by Neil McGovern

Digital businesses are defining launch plans for moving from standard data warehouses to enterprise data warehouses. If multiple data formats, automated business processes, real-time response, and self-service reporting are part of your business quest, SAP BW/4HANA can deliver.

“The data is out of date. You’ll have to start all over again.” When the audience hears that news in the Oscar-nominated movie Hidden Figures, we ache for Katherine Johnson. The expression on Taraji Henson’s face, the actress who plays Johnson, fully captures the frustration of pouring your energy and expertise into a time-sensitive project only to find out it was futile.

In the movie, set in the early 1960s, NASA is in a space race against the Russians. The real-life mathematician Johnson was responsible for checking the launch team’s math, reviewing reams of equations by hand with a pencil, paper, and her incredible analytical skills. You would think that 50-plus years later, data would be our most powerful ally. Yet, while we have sent humans to the moon successfully, gravity has kept businesses from truly exploring their data warehousing capabilities.

The weakness isn’t due to poor investments. Companies are heavily invested in collecting data through Hadoop, but the data stays locked up in cold storage and it doesn’t mingle with business data. That separation of Hadoop data and business data is preventing businesses from making data-driven decisions.

The incredibly short life span of data is another contributor to current data warehouse limits. Companies that run their business from batch reports based on yesterday’s data are losing races to business that live in a zero-batch world. Competitors are collecting and analyzing huge sets of structured and unstructured data in real time—and they are realizing better business outcomes.

The new launch goal is to have an enterprise data warehouse (EDW), and the target is transitioning to a digital business. A comprehensive EDW platform, such as SAP BW4/4HANA provides the structure that digital businesses need to transform their companies. These four before- and after-scenarios explain how EDWs move organizations out of the past and into a successful future.

How you handle your Hadoop data determines your viability.

Businesses have invested heavily in Hadoop-based platforms that collect every type of data. What’s missing, though, is mingling that data with the extremely valuable business data. SAP BW4/HANA brings all the data together so business data can be merged and analyzed with the Hadoop data.

A global cosmetic company, for example, can create an app that connects body, fashion, and health. Retail sales and traditional advertising no longer create effective brand awareness, customer loyalty, or revenue increases. Without the customer data stored in the company’s business systems, it could not create a sophisticated, personalized beauty app. SAP BW/4HANA allows the combination of data from purchases, customer demographics, store locations, fashion news, and health resources. By analyzing all the incoming data, the company can identify and respond to customer needs more quickly with personalized services and products that move as the market moves.

Transitioning to automatic business processes from manual ones is fundamental to success.

Oil and gas companies are transforming their businesses by adjusting how they inspect, maintain, and repair equipment. Like many businesses, these companies schedule regular inspections that send a technical crew to remote areas. The team looks over the equipment and makes any necessary repairs or adjustments. This process works fine—unless the equipment ignored the human-defined schedule and failed without warning. In these circumstances, companies paid a huge price tag to get a crew to the site as fast as possible.

Digital oil and gas companies automatically track equipment measurements at remote sites. When temperature readings, vibrations, gas emissions or other measurements move outside of a healthy range, the maintenance crew receives an alert. The staff can decide to send out a maintenance crew if necessary.

Manufacturers have followed suit, automating communications across suppliers. A computer manufacturer, for example, can adapt as necessary if a chip manufacturer has a drop in inventory. As soon as the chip company realizes it will not fulfill its order, it automatically alerts everyone in the supply chain. The computer manufacturer can respond by looking for another supplier, alerting marketing to adjust promotions, and warning sales who may need to adjust forecasting. In a digital business these communications flow automatically throughout the supply chain bypassing any human delays.

Self-service reports must be available for anyone who needs them.

Reports rarely get into the hands of the people that really need them, and too often the information in them is out of date. Digital businesses let non-technical staff run the reports they need that help their business group and the company have better business outcomes. An analyst in the mobile banking group can ask, if we raise the fee on overdraft alerts, how much will revenue increase and how much customer churn can we expect? A city planner can ask, if we add a stop light at this intersection, how many accidents could be avoided? A business analyst can ask if we reduce the temperature at a specific time every day, we can lower our energy bills by how much?

The future will include predictive analytics and machine learning.

Digital businesses are already looking at what else they can do with their data, and much of the excitement centers around predictive analytics and machine learning. SAP BW/4HANA prepares businesses for these enhanced analytic capabilities.

Soon, airports, for example, may add machine learning to improve security. Instead of searching for dangerous items that create long lines of passengers, they want to cross check the airport and identify risky passenger behavior. In the ideal scenario, airports would build a 360-degree view of each person. Data collected would be security screenings, behavior tracking, information from other sources such as bookings, travel history, and so on. By applying predictive analytics and reviewing these large sets of structured and unstructured data, airport security would grade each person on their risk potential.

Cities are joining the move to machine learning to predict car thefts, identify national trends for burglaries, and forecast staffing requirements. Security staff can decide which areas most need patrol teams and can identify hot spots and patterns by the location and timing of crimes. Sentiment data, data based on social media feed, is also added to the mix so that the communications department can track the group’s online reputation.

The Next Step in Business Transformation

This is just a glimpse of the transformation that can occur with an enterprise data warehouse, supported by SAP BW/4HANA. If you are looking to simplify your business warehouse strategy and currently run SAP BW or want to migrate to SAP BW/4HANA from another EDW, you can find additional information by accessing a white paper titled “SAP BW/4HANA: the top 10 considerations.” This great resource offers technical tips and insight about working with SAP BW/4HANA and narrows the must-know information into 10 considerations for moving to SAP BW/4HANA.

Neil McGovern is senior director of Product Marketing, SAP HANA Data Warehousing

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