The digital economy is a data economy. Companies that survive and thrive today know how to leverage their data for analytics and actionable business insights. These insights can be used to improve customer experiences, reduce costs, or even drive new business models that disrupt industries and displace the competition.

But more than ever, the data on which this insight is based is spread out across ever-proliferating sources. The result is a gap between the business demand for more insight and IT’s ability to deliver.

Data, Data Everywhere

The good news for IT is that the solution to this problem may very well lie in stepping aside. But more on that later. First, let’s see what we’re up against.

A quick look at the various kinds and sources of data out there paints a picture of an exceptionally differentiated data landscape. Begin with traditional data sources from tried-and-true business systems. These include systems for ERP, CRM, supply chain, point of sale, product lifecycle management, customer service/call center, and so forth. Add in e-mail, website statistics, and e-commerce. Now you have a mix of structured and unstructured data.

Include the data from new channels of customer interaction—product platforms, mobile apps, social media, gaming systems. And don’t forget the internet of things (IoT). If you’re using sensors in plant equipment or wearables, for example, then count this as another major new data source to manage.

The Old and the New of Data Warehousing

That’s a lot of data—and the fact is, old ways of managing it for analytics and insights are standing in the way of IT delivering better service. Many companies still depend on a decades-old approach to data warehousing where data is replicated and stored in silos—on disk and on premise. Today, we need new approaches.

Fortunately, the digital economy is not just a data economy. It’s also an economy of emerging technologies. Some of these technologies—social media, IoT, artificial intelligence—exacerbate data management challenges. Others are helping to address them.

Take, for instance, in-memory data processing and cloud access. With the price of active compute memory dropping, it’s been feasible for some time for companies to store large volumes of critical data directly in RAM. And with cloud access added in, you can find data warehousing faster, simpler, and more agile.

It’s faster because instead of moving all data to the data warehouse, you can virtualize whatever data model you need, keep the source data in a data lake, and run your calculations on the fly. It’s simpler because it reduces the footprint of your data management layer—while your critical data (most of it) can be stored centrally in the cloud. And it’s more agile because it allows you to change what to analyze next as quickly as you can think of it.

With these advantages, IT can now meet demand for insight more effectively. What does this mean for the business? Let’s say you’re a product manager and you want to analyze performance of your product in the market. Traditionally, you might focus exclusively on sales and profit margin. But now, with new approaches to data warehousing, you can also easily pull in data from social media for sentiment analysis. This can expand the picture considerably.

For example, you could analyze performance across regions using both using the combined analysis of sales and financials on one hand and social media on the other. Maybe you spot places where the sentiment is high (people love your product), but financial performance is low. Hmmm. What could this mean? Maybe it’s a problem with distribution—and maybe fixing this problem could boost sales.

Empowered Business Users

Notice that the product manager in this admittedly simplified example is acting on her own—which brings us back to the idea of IT stepping aside. It’s not that IT throws its hands up and abdicates responsibility for data management. Quite the opposite: when it comes to the issues of concern for IT—such as security, availability, and scalability—IT remains in control. This is important because security, availability, and scalability are what underpins the timely, trusted, and actionable insights the business requires.

Meanwhile, new user interfaces, with visualization tools that aid understanding, make self-service a reality. Now business users can view and work with easily accessible, virtualized views of data as needed for business purposes—without IT stepping in to create duplicates and silos that add to the complexity of data management.

By stepping aside in this sense, IT empowers business users to leverage company data for new purposes, such as delivering a better customer experience. And this is what helps make IT a hero. Not bad.

Learn More

  • Download a new SAP-commissioned thought leadership study from Forrester Consulting: “How To Become An Insights-Driven Business.”
  • Watch the replay of the recent webinar, “Take Your Business from Data-Driven to Insight-Driven,” where you’ll hear insights from experts from Forrester Consulting, Valvoline, and SAP.

This article originally appeared in the SAP D!gitalist Magazine and has been republished with permission.

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