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3 Factors That Lead to Enterprise-Wide Data Self-Service Analytics Capability

Posted by Brooke Lester on Jan 22, 2019 11:36 AM

3 Factors That Lead to Enterprise-Wide Data Self-Service Analytics Capability

Take a second to think about what your current data request process looks like. Does your staff have to constantly ask IT to run queries to access the internal data they need for mission-critical tasks? Or, can they get what they need on their own through self-service capabilities?

If you answered “yes” to the first question and “no” to the second, it is time to think about what it would take to achieve self-service capabilities. Read on to learn the three factors that lead to enterprise-wide data self-service analytics capabilities to increase efficiency and productivity.

A Single Source of Truth

To empower self-service data analytics, you need data integration first and foremost. In many cases, enterprise data is stored in silos. That is incredibly unhelpful; you cannot understand what is going on across the company if you only see a very small part of the picture.

Data integration creates a single source of truth. It puts an end to redundancies, mistakes, inconsistencies, and other barriers that plague the enterprise. A single source of truth enables self-service analytics across the enterprise because employees see a broader picture that allows them to make better decisions.

A Robust Cloud-Based Infrastructure

One of the components that allow you to achieve self-service analytics capability is a robust cloud-based infrastructure. We will illustrate with a real-life example.

The social media giant Facebook relied on a massive infrastructure for its data analytics. Decision-makers realized that their infrastructure could not scale, which was problematic as Facebook experienced explosive growth. The company switched to Hadoop, cloud-based analytics software; that shift allowed employees across the organization to access information and analyze it.

One of the benefits of the cloud is that it is easy, convenient, and cost-effective to scale. If you want more employees to be able to analyze information on their own, the cloud is a good option.

Technology that Facilitates AI and Related Innovations

AI has moved out of the realm of science fiction and into the enterprise. Companies across the world are utilizing it on a day-to-day basis for a wide variety of business processes. One of those processes is self-service analytics.

How can AI and related innovations help? For a start, machine learning (the ability of a machine to come to conclusions on its own without human intervention) can investigate computers and devices linked to the network, examine data sources, classify information, and inform employees what information they need to gain access to that data. Machine learning can ensure compliance with privacy and security policies while allowing the people who need the data most to access it.

Self-service data analytics lead to gains in productivity and efficiency. With the ability to access information on their own and analyze it without the aid of the IT department, employees can get so much more done in less time. Data integration is one of the components that power self-service analytics.

REMEDI has recently partnered with a leading solution provider to bring you visibility tool options. To learn more about how data integration impacts the success of your enterprise, you can take a look at some of our recent data integration success stories and contact us to discuss your integration and visibility needs today.

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