What ChatGPT Thinks Can Happen at Your Organization without Datalogz?

A company's BI team can face a catastrophic data crisis due to duplicate datasets, security issues, stale data, uncertified assets, and inaccuracies in reports. Don't let this happen to you!

What ChatGPT Thinks Can Happen at Your Organization without Datalogz?
Photo by regularguy.eth / Unsplash

We asked ChatGPT about a series of unfortunate events that happened to a BI Team that has not started using Datalogz.

Hopefully, nothing like this has happened to you. Nevertheless, similar instances have indeed occurred to many of our team members in other data roles.

“BI Team's Catastrophic Data Woes”

A mid-sized manufacturing company’s BI team managed their data and reporting using PowerBI, Tableau, and Looker for several years with excellent success. However, over time, they began to encounter several issues that caused a ripple effect of problems that grew worse and worse.

It all started when the company experienced a sudden spike in data consumption. The BI team scrambled to optimize their datasets, but in the process, they discovered several duplicate datasets that were causing unnecessary clutter and confusion. They quickly deleted the duplicates, but not before some report creators had used them to produce inaccurate reports.

The duplicate dataset issue persisted as report creators continued to accidentally duplicate datasets due to naming convention issues, permission issues, schema issues, ownership issues, and source issues. Meanwhile, the team struggled to keep up with failed refreshes due to the massive amounts of data being processed.

To make matters worse, the company’s security team detected untrusted IP access to the BI systems, indicating a potential data breach. The team scrambled to investigate and discovered that several unused datasets and dashboards were accessible to unauthorized users. The company was forced to temporarily shut down its BI systems, resulting in lost productivity and missed deadlines.

As the BI team worked to address the security issues, they discovered that several datasets contained stale data, causing inaccuracies in reports used to make critical business decisions. Additionally, they found that several assets were uncertified and should not have been used for reporting, leading to further inaccuracies and confusion among users.

The BI team tried their best to address all of these issues, but the problems kept piling up. As a result, the company lost trust in their data and reporting, causing customers to lose faith in their products and leading to a drop in sales. The company was forced to lay off employees and eventually declared bankruptcy, unable to recover from the financial losses caused by inaccurate reporting and lost productivity.

Yikes! Dark turn there at the end. Let’s avoid this future together.

Begin using Datalogz now!


Subscribe to Data Dive

Interesting data concepts, avant-garde ideas, and the best of data content from across the web.