And what it actually means is "visualizations and dashboards". Why make decisions based on analyzing the data from a report when you can get a vague impression from a pretty chart and go with that instead?
IMX, the core problem is that all BI software is built around the idea that everything is a financial value that can always be arbitrarily aggregated meaningfully, and that looking pretty is more important than presenting the data in a way that your organization actually finds logical.
It's a way to sell very expensive software to decision-makers, while also producing software complex enough that it can't be configured well enough to properly evaluate until well after you've already bought it. Only then do you find that the feature set is very broad, but very shallow. It's only 18 months later that you discover how limited the report writer is, or that you have to do it this one way for everything even if you really could use it formatted slightly differently.
It's like using a pivot table in Excel and trying to control the order of the columns, or to make one table aggregate two values distinctly, etc. You end up with 10 seconds to pull your data and create the table, and 4 hours trying to get it to display in the manner you want before giving up.
> IMX, the core problem is that all BI software is built around the idea that everything is a financial value that can always be arbitrarily aggregated meaningfully, and that looking pretty is more important than presenting the data in a way that your organization actually finds logical.
I used to work directly modeling data for various sized companies on behalf of two different BI sellers.
As I see it there are perpetually two problems:
1. BI is marketed at and sold to anyone needing any kind of data visualization capabilities, and most packages I've worked with can do this but that's not really where they shine.
2. They really shine when you have huge amounts of data stored in different systems and you are trying to build an environment up where you can coalesce that data into one place and then visualize it, and you need to routinely report on these sorts of things.
I think most BI solutions fall into the same space as JIRA does -- highly-customizable solutions that are sold as "Turn-key" without any warning ahead of time that it'll require someone (or several people) on your team become ridiculous levels of expert in areas that don't necessarily help the business.
It's a specialized skill most places don't really need when what they're looking for is a simple reporting package that can connect to just any database.
Similarly, I saw a lot of people with BI insisting they had "Big Data" and thus "needed" things like Hadoop in order to process their stuff, when in reality the MySQL, SQL Server, or Oracle DB they were already invested in would do the same job faster 99.9999% of the time.
Where I've worked BI wasn't ever used by decision makers. It's used to make dashboards that are part of a sales pitch to clients, because clients love pretty pictures and "science".
That largely depends on the culture of the company. I've been at places that used BI to make decisions, and other places that just used it to nitpick over events from years ago.
BI, like every other tool doesn't exist in a vacuum. It has to be present in an environment that has peopeople that know how to help themselves use the self-service attributes (i.e not Boomers), it also has to occur in a culture where KPIs and metrics are understood, and used in day-to-day discussions of the business, there should also be a training component to deploying your BI solution too.
Without these aspects being present, your BI solution will devolve into either a sales prop with pretty colors, or it will become a web version of Excel.
Where I used to work I feel like it was actually used. And it gave some surprises to deals that were until then seen as profitable.
I worked with consumer apps and it was used for making business decisions related to return of investment and marketing.
But it took some time to get there and before that I think most decisions were based on questionable assumptions from half-baked results.
What was the final building bricks were to be able to calculate the lifetime value of recently acquired users, but also to collect all the types of revenue and cost and through various tricks (based on user base numbers mostly) break it down into countries and marketing channels.
IMX, the core problem is that all BI software is built around the idea that everything is a financial value that can always be arbitrarily aggregated meaningfully, and that looking pretty is more important than presenting the data in a way that your organization actually finds logical.
It's a way to sell very expensive software to decision-makers, while also producing software complex enough that it can't be configured well enough to properly evaluate until well after you've already bought it. Only then do you find that the feature set is very broad, but very shallow. It's only 18 months later that you discover how limited the report writer is, or that you have to do it this one way for everything even if you really could use it formatted slightly differently.
It's like using a pivot table in Excel and trying to control the order of the columns, or to make one table aggregate two values distinctly, etc. You end up with 10 seconds to pull your data and create the table, and 4 hours trying to get it to display in the manner you want before giving up.