Why Proper Data Provisioning is the Analytics Tipping Point

data provisioning

In today’s business climate, every organization is looking for data-driven insights to maintain a competitive advantage.

And that puts increasing pressure on business analysts to find and refine data with limited resources and under tight deadlines.

Enterprises miss too many opportunities to out-think their rivals because it takes much too long for business analysts to get the data they need from the massive amounts of structured and unstructured data flowing into the business from various sources every day.

In general, analysts spend 40 percent to 60 percent of their time just preparing data instead of doing high-value activities such as data analysis and model building for the rest of the organization, according to Blue Hill Research.

In fact, the typical data analyst spends at least two hours a day on data provisioning activities – extrapolated over a year (assuming about 250 working days in a year) that adds up to over 500 hours a year per analyst, according to Blue Hill Research.

The goal of business intelligence has always been easy, self-service access to data. With data prep, companies are able to re-imagine how they collect, prepare, analyze and use big data to drive business value.

With proper data provisioning, business analysts can focus their time on asking more questions of their data and, more importantly, deriving the important insights about their businesses to keep ahead of the competition.

Self-service data preparation tools add context to the data, thereby helping organizations move from randomly searching for information to more productive strategies to uncover valuable business insights.

Proper data provisioning lets enterprises improve the entire analytic process, enabling them to identify business problems and achieve business results in hours, not days or weeks.

Analysts who switch from preparing data via spreadsheets and/or hand-coding to a dedicated preparation solution realize impressive results, said James Haight, principal analyst at Blue Hill Research.

“In general, those who made the switch to a dedicated solution cut their data preparation time at least by 50 percent,” he said. “Given the complexity and volume of data that today’s analysts encounter, investing in the help of dedicated functionality can be a significant time-saver.”