The Case for Agile & Self-Service BI

The Case for Agile & Self-Service BI

The Case for Agile & Self-Service BI

I was on a call with a client who was trying to consolidate dozens of transactional systems into a single model to support a more effective reporting paradigm. The envisioned solution focused on self-service, visual analytics, while also supporting more traditional reporting.

This client’s challenges were similar to what many other businesses face today. They wanted:

The client wasn’t questioning whether or not there was value in the project ahead. Their questions were focused on the best approach. Do we pursue a big bang approach, or pursue something more agile in nature?

Upon further discussion and reflection, the objectives of the program seemed to be a perfect case for agile. Let’s talk about why.

While the client knew the value of the project, we discussed how, in reality, data projects can die on the vine when the value isn’t apparent to the business funding the initiative, or the IT executives who need to demonstrate their operational ROI. As such, the ability to demonstrate value early and often becomes critical to building and keeping the momentum necessary to drive projects and programs across the finish line.

Read Also:
Top 9 ethical issues in artificial intelligence

Project sponsors need to constantly be selling the value up to their management and across to the ultimate customer. Iterative wins become selling points that allow them to do so.

To truly understand what can be delivered (and by when) means accurately assessing how much work is in front of you, and how quickly your team can deliver with quality.

This example project was as new as the client’s team. For them, the most logical approach was to start doing the work to learn more about the work itself as well as the team. After a few iterations, the answers to the following questions become clearer:

Anyone who relies on data, whether they are business or IT, have their go-to sources that they rely on. To get an individual to embrace a new source for all of their information and reporting needs requires that the new source be intuitive to use, performant, and above all, trustworthy.

Read Also:
Can Master Data Management and entity analytics be self-service?

 



Chief Analytics Officer Europe

25
Apr
2017
Chief Analytics Officer Europe

15% off with code 7WDCAO17

Read Also:
How to Make a Client-Centric Transition to the Cloud

Chief Analytics Officer Spring 2017

2
May
2017
Chief Analytics Officer Spring 2017

15% off with code MP15

Read Also:
Beginner's guide to the history of data science

Big Data and Analytics for Healthcare Philadelphia

17
May
2017
Big Data and Analytics for Healthcare Philadelphia

$200 off with code DATA200

Read Also:
Is machine learning the next commodity?

SMX London

23
May
2017
SMX London

10% off with code 7WDATASMX

Read Also:
A perfect illustration of how the big data value chain works

Data Science Congress 2017

5
Jun
2017
Data Science Congress 2017

20% off with code 7wdata_DSC2017

Read Also:
When is real-time analytics the right analytics?

Comments 1

  1. Roland C Bullivant

Leave a Reply

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