What’s just as bad, or even worse, than not having access to BI and analytic technology?

Having access to too much BI and analytics technology. This is the situation most businesses are in. The ugly truth is that the average business plays host to a plethora of BI and analytics tools. Maybe they’re lucky and they’re able to make do with just Tableau + Excel + Microsoft’s traditional SQL Server BI stack. Maybe it’s Tableau + Qlik Sense + Excel + SQL Server, Oracle, etc. Maybe it’s PowerBI + Qlik + Excel. If a business is old enough, acquired a few businesses, or been through enough, it could be all of the above—plus Excel. In every case, Excel is an absolute necessity: how else can users prepare data to be shared with people using all of these other tools?

It’s ironic: Excel remains the most powerful (because ubiquitous) data integration tool going.

But wait, there’s more!

The previous example is just the tip of the iceberg. It focuses on self-service-type BI and analytic discovery tools. If it’s rare to find a completely homogeneous self-service environment, it’s rarer still to find a broader BI ecosystem that doesn’t also feature pockets of traditional BI tools, including Cognos, MicroStrategy, Qlik (the core Qlik product, as distinct to Qlik Sense), SAP BusinessObjects, SAS, and dozens of similar tools. The people who actually use these tools tend to like them. They’re well-versed in their strengths and quirks and don’t want to give them up. But a Cognos user knows Cognos—not SAP BusinessObjects; there’s almost no cross training between users of these tools. This is in spite of the fact that (in a large enough organization) you’re going to find Cognos and SAP BusinessObjects; MicroStrategy and SAS.

What’s the end result of this? Quite aside from squandering millions of dollars in CapEx on (upfront) licensing fees and (ongoing) maintenance costs, to say nothing of millions of dollars of additional CapEx on integration middleware from Informatica, IBM, SAP, SAS, Tibco, and others, this situation results in what I like to call “Lowest Common Denominator BI.” This is the grotesque scenario whereby business users are forced to dump their interactive, engaging visually appealing dashboards, visualizations, charts, etc. into (mostly) static PowerPoint slides or (completely static) PDF files. Why? Because they can’t share them otherwise.

It’s 2019: why the [expletive deleted] are we still doing this?!

It can’t be because we don’t have options or alternatives. If, as I believe, the battle is all but over and the winner in terms of seat volume will be a single platform of some kind—right now, that sure looks like Microsoft’s Power BI, although Google’s acquisition of Looker complicates things—then it’s reasonable to think that the business worker of tomorrow will finally have access to a modern BI tool that’s as ubiquitous (and extensible) as Excel is today. This would allow them to filter and format workbooks and dashboards to suit their own interests.

What this means is that businesses must either completely transition to and adopt Power BI (or Google BI + Looker, assuming Google manages to knit together its emerging cloud BI platform) or begin thinking about adopting and implementing a modern data management platform that is at once vendor-, interface-, location-, and API-agnostic. Microsoft (or Google) will urge the first course of action. Why wouldn’t they? A customer that standardizes (if only for the sake of convenience) on their platforms will probably stay put. The more they invest in Power BI or similar platform-specific solutions, the more they’re locked into those solutions.

This situation is being compounded by the ever-increasing presence of embedded analytics. Here bespoke visualization tools are tuned to a specific application, operational function or even an industry. For example, Adobe has become a dominant player in marketing analytics; SAP would like to own the manufacturing analytics leadership position; while companies like Domo have done well with CPG companies. What does the Salesforce acquisition of Tableau mean to that product’s future? A focus on sales analytics would make logical sense? Does this trend herald the end of general purpose BI tools or does it create evermore niche data and knowledge silos?

Again, it’s 2019—not 1989. Today, customers have plenty of viable choices, thanks to the availability of open standards, open architectures, competition in the cloud, and other factors.

Imagine a modern data management platform that speaks the language of the cloud (via RESTful service calls, or JSON, BSON, and other serialization formats); supports connectivity to stateful systems using ODBC, JDBC, and similar interfaces; and facilitates transparent access to data wherever it’s located (e.g., in an on-premises database, in an Amazon S3 object store, in the Salesforce SaaS cloud, etc.). With a unified data management platform layer, it would be possible to accommodate all BI tools, platforms, and services without disrupting the way people use these technologies—or depriving users of access to their favorite tools.

You can see where I’m going with this, right? This is where Unifi’s Data Platform plays a pivotal role in enabling organizations to leverage their existing data and analytics investments. By delivering an AI-driven data discovery and prep tool in a single platform, every user can find and use the data they need regardless of the BI tool or data science platform they are using.

Imagine a scenario where a knowledge worker goes to search for a specific Power BI report and discovers (via Unifi’s AI-powered data catalog) that this report only exists as a Tableau dashboard. No problem: they can use Unifi’s platform to transform the Tableau workbook into its Power BI equivalent. It’s as easy as clicking a few buttons and selecting Power BI as the output format. Unifi deconstructs the dashboard into source data and transformations, connects to those same source systems and runs the same transforms, and then formats the output into a PBX file—the native file format used by Power BI. Now the user can use the filter-and-select functions in their preferred tool (Power BI) to get the results they need.

No more data silos. No more BI silos. No more Knowledge silos. It sounds like magic, or the stuff of pipedreams, but it isn’t. It’s AI-powered common sense. And it’s doable today.