The trouble with self-service business intelligence -

The trouble with self-service business intelligence –

The trouble with self-service business intelligence -
Easy to do is easy to say.

Self-service analytics sounds like a great idea – empower employees to extract insights from organizational data without involving data scientists or data mining experts.  Once the IT department sets up the data sources, business users can access the data via a user-friendly interface and generate reports on their own.

What’s not so easy is balancing information governance with maximum agility for hundreds or thousands of agency workers.

Not so simple set up

The price organizations pay for self-service convenience is that someone must first load data into a box somewhere — be it a database-like server or a business analyst’s desktop.

This might sound straightforward enough, but to oversimplify what’s involved here is to ignore just why data integration (DI) is such a complex and often frustrating discipline. Integrating data isn’t as simple as downloading a tool such as Tableau, installing it on the desktop, and going out and grabbing data from SAP or PeopleSoft.

Read Also:
6 Ways To Make Your Company Data-Driven

Somehow, some way, someone has to build the plumbing. Even if it were easy to obtain and configure access — to get the appropriate credentials, to configure a connection to an SAP system and to begin siphoning data — it isn’t at all easy to join data.

“There is a big myth in self-service which is that you can just somehow open a big database and the users are going to go make sense out of it,” said Philip Russom, director of research for data management at TDWI, a sister site to GCN. “Typically, there has to be a lot of prep work to get something in place. It doesn’t matter what kind of self-service it is. IT, data people, whoever –technical people — have to do a fair amount of prep work to get at it and make it available.”

This is where self-service discovery breaks down — and why self-service data prep technologies (such as those marketed by Alteryx, Paxata, Trifacta and others) have received so much attention.

Read Also:
Data science in the cloud

Traditionally, the only way to join data when using self-service tools such as Qlik or Tableau was to use the vendor’s back-end scripting facility. Unlike the easy-to-use front-end offerings, these tools were much more complex, meaning analysts needed both business and technical expertise to use them effectively.

The challenge for vendors is to transform the features they’ve traditionally exposed as part of the end-user-oriented self-service experience into enterprise-grade services that emphasize reuse, repeatability and manageability.

Another issue is that self-service tools are designed primarily for looking at or transforming data — not for managing it.

Read Full Story…


Leave a Reply

Your email address will not be published. Required fields are marked *