Today’s businesses aspire to be “data-driven,” but what does that really mean? In today’s terms, a data-driven business is one that uses data across the organization to:
- Quickly iterate existing product lines to address new markets
- Optimize supply chains to meet dynamic geopolitical conditions
- Providing personalized experiences to consumers at an enterprise scale
- And more
The key is a strong data and analytics culture, producing vital information that informs decision-making and behavior throughout the business. But a failure of analytics can open up information gaps that divide teams and silo data, leaving enterprises in the dark and struggling to catch up as their data-savvy competitors seize new opportunities and widen their lead in the market.
Mind the Information Gap
Data alone is not the same as information.
Information = Data + Context
For example at a bank, data includes a customer’s name, the number of accounts that person holds, the amount of money they save or spend, and the transactions they conduct every month. Information is what that data combined can tell you: Whether that person is a loan risk, whether they’re about to take their business to another bank, whether they’re a good candidate for a credit card or a better rate.
Analytics is the act of turning data into useful and timely information that is circulating throughout your organization. If all of the parts of your information engine are humming–data, technology, people, processes–analyzing and modeling data results in useful and timely information circulating throughout your organization.
If any part of that engine breaks down, you might end up with an Information Gap. You have the data, and you have users waiting for insight. But there are barriers in the middle that prevent data from becoming the information that leads to insight, including:
- Siloed data
- Poorly prepared data
- Lack of communication and collaboration between teams
- Duplicated data, or too many sources of the truth
5 telltale signs of Information Gaps
Do you have an Information Gap (or more than one) in your enterprise? If any of these scenarios sound familiar, you may have some gaps to fill:
- There’s a lag time between coming up with a data product and getting it into production. Forty percent of companies say it takes a month or more to deploy a machine learning model into production.*
- Your data engineering team, your data scientists, and your business analysts are all using data from the same applications…from different points in time, in different datasets.
- Your business bases decisions on a statistic or bit of insight. No one has any idea where it came from.
- Information comes straight from the data engineering team into a dashboard, where it gets shared selectively by those who can see it.
- The numbers in that dashboard have zero correlation with what end users are seeing on the front lines.
If any of these things are present in your organization, it’s possible that data is not getting where it needs to be, and not in a format that’s useful for modern analytics. If Information Gaps are present, it’s still possible for your organization to struggle with analytics and accurate insight, even if you have made a move to the cloud.
How to bridge the gaps
One surefire way to overcome information gaps in your organization is to speed up analytics productivity and provide the entire business with trusted datasets that are shared, secured, and connected. Matillion ETL can help. To read more about Information Gaps and how cloud-native ELT can help you close them, download our latest ebook, Close the Information Gap: How to Succeed in Cloud Analytics.
*“The 2020 state of enterprise machine learning,” Algorithmia, October 2019.