SAP Data Hub: Sharpening the Data Landscape View

Greg McStravick

Posted by Greg McStravick on September 25, 2017

President, SAP Database And Data Management

More by this author

A recently conducted a study of IT decision makers from enterprise level companies that found the following:

  • 74 percent say their data landscape is so complex it limits agility;
  • 86 percent say there is much more they can do with their data;
  • 50 percent believe that data is inaccessible to a wide variety of business stakeholders.

Those numbers are shocking. Why don’t these enterprises have better access to and use of their data?

For one thing, archaic architectural data landscapes make it nearly impossible. It’s an incredibly complex process, combining data lakes, warehouses, data stores, data marts and systems of records in real time, and combining those data sources at point of need is virtually impossible.

Complicating matters are three major components: governance, data pipelines, and data sharing.

  • You need to know who changed the data, who used the data, and what was changed. For example, an analyst in an organization looking at a finance average trying to determine: who calculated that avenge? How was this average calculated? Who changed the data? Who sourced it? And why did they use a particular set of data?
  • Data pipelines. Refining data means moving it from raw data to candidate data. For example, making use of sensor data in machinery. How do you turn that raw data into candidate data that’s usable, by somebody in the business or a data scientist? You can do some of this today, but it’s manual, its expensive and it’s timely.
  • How do you achieve accessibility, connectivity and harmonization of data across systems? One very basic example is a date – May 5, 2017 in one system is 05/05/17 in another system. How do you harmonize that, and do it thousands of times?

Hearing from our customers about those overwhelming challenges, we had to come up with a solution in the market to solve for that. And we believe we’ve done it.

This week, we unveiled SAP Data Hub, a simpler, more scalable approach to data landscape management eases integration burdens and provides better enterprise-wide landscape visibility and governance.

SAP Data Hub is the way that we are rearchitecting a way to handle complex data landscapes and how to manage data so it becomes a catalyst for business transformation, not a barrier to business execution.

We’re addressing governance with centralized visibility into the lineage of the data, allowing users a unified view to understand how data was changed, how it was sourced, who changed it, why they changed it when they changed it.

We’re offering powerful pipelines with distributed, push down processing, which allows users to move from a world of centralized data to centralized governance, leaving the data where it is, bringing together myriad sources – some we may not even know of yet – together.  SAP Data Hub’s open architecture enables the management of modern, hybrid heterogenous data landscapes, bridging the bi-model IT divide.

Lastly, the design intent of Data Hub is to enable data sharing, leveraging existing connections and integration tools to combine these data sources. Each system’s data catalog is registered to Data Hub, which makes it easier to add new systems over time and leverage them quickly with existing systems. Furthermore, it leaves the data where it resides, whether it’s on cloud, on premise or in a hybrid environment.

In this modern world businesses are operating in, where data is doubling every two years, and the sources of data are as creative and varied as your mind will allow you to think, the management and use of that data has to change. In addition to many of the tools we’ve already introduced, including SAP HANA, SAP Data Hub is THE solution to bring data together in real time, leverage it for point in need for the business user and – most importantly – create value for the enterprise.

VN:F [1.9.22_1171]
Average User Rating
Rating: 3.8/5 (4 votes cast)
SAP Data Hub: Sharpening the Data Landscape View, 3.8 out of 5 based on 4 ratings