BI Automation on the Rise: Can you afford to lag behind?

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Just over a year ago, IDC’s forecast showed that by 2025, total worldwide data will “swell to 163ZB, 10 times the amount today.” The response we’d expect from your given CIO would be something along the lines of “if we want to stay in the game, we’ve got to make our data management, and even our metadata management, an ultimate priority. Our data needs to stay as efficient, accessible, and safe as possible, so that we’ll be ready for the meteoric rise ahead. Let’s leverage BI Automation to optimize our databases.”

But what are CIOs actually saying

 

Can you afford to lag behind the power of BI Automation?

The response is simple: “There’s not enough budget for BI Automation. We recognize the importance of optimizing our data quality and accuracy, but we can’t afford it. Let our BI team work harder, and manually breed the same results that machine learning algorithms are capable of.”

 

As metadata management and data governance enthusiasts, we wonder: Can business executives really afford business mistakes caused by inaccurate data?

 

“It’s an anomaly”, says Octopai CEO Amnon Drori.

“On the one hand, CIOs understand the power of BI tools that are built to accommodate their rapidly growing data about user activity and business performance. Yet, they still conclude that instead of empowering their BI teams with the ability to more efficiently map out all data reports and locate this information instantly, with the complete, accurate data lineage from every single reporting system — they’d rather let their BI teams slave away with no end in sight.”

 

What BI looks like in 2018

BI has always been designed to deal with data management challenges on an infrastructure level. By virtue of the word business intelligence, its inherent purpose is to improve business results. Isn’t this the ultimate goal of the CIO, and the executive leadership at large?

 

If so, why are information experts such as CIOs settling for outdated technologies? Do they realize the difference(s) between results generated manually by BI professionals versus automatic metadata discovery tools?

 

Click here: See how Octopai is transforming BI

 

Faster than ever

On September 20th, Ketan Karkhanis, General Manager at Salesforce Analytics explained how “AI is finally making the analytics needs of the modern business user a reality.

The difference between AI tools and the outdated analytics tools that generate visualizations are that the latter “were built for simpler days….the world has moved on. A digital business of today needs to connect with its customers in a whole new way, faster than ever. And to do that, you need intelligence at every point of decision-making.”  

 

When it comes to the power of BI, what does “intelligence at every point of decision-making” mean in practice?

 

It means data lineage you can rely on, data governance that ticks every box and regulation, and of course, error-free data that is checked and verified by automated metadata discovery.

Let your data work harder, Mr. CIO, and not your BI team. Your dedicated employees have enough on their plate when it comes to keeping your databases up to shape. If business performance is really so important, then get smarter about it, and fast.

 

More on metadata management:

VIDEO: Nix Inaccurate Reporting with Automated Data Lineage

State of BI 2018: Metadata Driving Data Discovery

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