Data Discovery has been great for the analysts in our organizations and has revolutionized the way they access, interact, and interpret data. However, I’ve always been more interested in serving the needs of the non-analysts.
In a meeting last week one of our partners, Musgrave Analytics, mentioned something that caught my attention: people are afraid to deploy dashboards to business users until the data is perfect.
Although understandable, the problem with this approach is that it can paralyze dashboard and other business intelligence projects and result in a frustrated business community that lacks access to critical information.
But today, with data stored not only on premise but increasingly in the cloud too (e.g. Salesforce, Marketo, Eloqua, Google Analytics), how do you access all of this data to create a consolidated view of your business?
We live at a time where there is vastly more information available than ever before. Tech trends like the Internet of Things are taking us into a world of connectedness, and everyone from Gartner to IDC are predicting big stuff for “the Things” in 2015.
In fact there is already far too much information out there for us to be able to meaningfully take it all in. However it is increasingly important that we use as much of this data as we can to avoid being left behind in both our work and our personal lives.
One of the most important things to do with information is to make it accessible right across your organisation in a way that allows users to “just use it”.
It feels like we are moving towards a “BI for analysts only” culture, so I feel compelled to ask: Is analysis just for analysts?
Petr Podrouzek wrote the first in a series of thirteen articles about agile business intelligence (BI) a few days ago. In this first article, Agile for BI is recommended by the experts, but is it used in the real world?, Petr points out that through his six years of working on BI projects he has never seen agile BI in use. To further his argument he says that many BI projects start out with an agile approach but that this is quickly abandoned in favor of the traditional waterfall model, where requirements are collected and a data model is developed followed by data sourcing and development of ETLs.
As Petr points out, this slow and excruciating process takes up precious time from everyone involved. And at the end of the day the customers, the ones who depend on your dashboards and reports, are left disappointed.
Thanks to a tweet last week from Cindi Howson, I discovered The Battle of Business Intelligence: Data Discovery vs. Traditional BI written by Southard Jones from Birst. The article provides a nice overview of how Data Discovery evolved and moved into the BI mainstream but most interestingly it argues that “Data Discovery remains one small piece of the larger pie that is business intelligence” !
Thank goodness for that, finally someone else saying that Data Discovery is not the be all and end all of BI. We were beginning to think we were the only ones Continue reading
A few weeks ago, @startupvitamins tweeted a great quote :-
And no-where is this more true than end-user Business Intelligence (BI). It makes sense for analysts to carve out the time to sit down and learn generic data analysis tools as they form a central part of their jobs. But for the rest of us, with operational responsibilities, things are different, we need BI which we can just use, without explanation.
Here at Antivia we have been championing this for the last few years, (read pretty much any of our other blog posts to see what I mean). Our product DecisionPoint does exactly this, it allows you to quickly and easily create easy-to-use, no-training-required BI apps and dashboards that you don’t have to explain to end-users. Continue reading