Employing Data Management and Analytics Technologies

Weekly average - 12 of 15 hours wasted managing dta, not analyzing it

19%  of  Analyzing

81% of 
Managing data
  • 20% Searching
  • 37% Preparing
  • 24% Protecting

Free for IDC’s IEP clients.

Not a current customer?

Gain a comprehensive understanding of the options and suppliers and their most effective use, so you can choose the right technologies for your organization.

Overcome Roadblocks

Investments in analytics and artificial intelligence are driven by the promise, opportunity, and excitement of a new wave of automation that not only drives inefficiency out of processes but also changes how people interact with the digitized world around them and how processes and whole ecosystems change because of automation. However, investment will be moderated by shortage of algorithm training data, outdated legal frameworks, shortage of analytics staff, behavioral biases, and insufficient attention to analytic orientation and data literacy.

What: This module will help high-level IT leaders choose appropriate technologies and suppliers through an understanding of key data management options. Employing the Appropriate Data Management and Analytics for your organization will requires a comprehensive understanding of the technology and supplier options for options such as analytic and performance management applications, data management and integration, along with business intelligence and analytic tools.

Why: 80% of time is spent on data discovery, preparation, and protection, and only 20% of time is spent on actual analytics and getting to insight. Much of the spent managing data is wasted; up to 12 hours per week because people cannot find, prepare, or protect data. Data intelligence software has the potential to change this ratio, providing users with the ability to find data easier and understand context and definitions for better integration, resulting in faster, more useful intelligence.

How: Making appropriate technology selections involves the following steps:

  • Create Data as a Service Offerings (DaaS)
  • Understand Your Data Management Technology Options and Suppliers
  • Understand Your Data Analytics Options

Successful DX efforts have measurable, achievable and
supported goals, strategy and KPIs