Making the shift to data-driven infrastructure seems like the obvious choice for enterprises. However, significant challenges exist in extracting real value from the data companies already have. Data complexity along with the combination of legacy systems coupled with new data solutions are keeping insights locked up.
Barriers to Data Integration
Organizations focus on collecting data, but lack the infrastructure to transform it into real-time value
This lack of insight creates pressure to collect more data, different data, better data, but insight remains elusive.
Gathering data isn't the problem. The real challenge is putting it to use.
Organizations are still locked in something we call "past analysis."
- Step 1: Ask a question.
- Step 2: Gather relevant data.
- Step 3: Deploy an algorithm to run for weeks or months.
- Step 4: Look back on those insights and attempt to make a decision.
- Step 5: Discover a missed opportunity to act on a critical trend or fail to act swiftly for a disruption. Now, it’s too late.
This is a good enough approach to historical data, but as all companies far and wide begin to leverage data to make decisions, it's not enough to make a decision. That decision must be swift, innovative, and in real-time (if not ahead of its time).
Organizations have real barriers to becoming data-driven:
- Data integration challenges – Data is complex in both volume and variety.
- Privacy and regulation – Ever changing regulations can cause serious risk, leaving some organizations to error on the side of locking data away from those that need it most.
- Poor quality – Real-time insight requires a steady stream of high-quality data. A lack can cost a company just as much as no data at all!
- Incompatibility – The more companies deploy shiny new solutions to data issues, the harder it is to integrate and keep up with them all.
- Limited self-service – Data literate companies need to allow all relevant departments access to data, but privacy or security concerns can hold them back.
Data Fabrics Open the Door for to Use Data
According to Gartner, a well-designed Data Fabric can provide the scalability and the flexibility businesses need. However, many organizations struggle to conceptualize how a Data Fabric truly works.
A Data Fabric connects current and past data solutions—overlaying the complex network that’s been created with data. It creates cohesion by:
- Securing data across the enterprise
- Providing a single view of trusted data
- Creating trusted data through automation (clean, systematize, and deliver data in real-time)
- Enabling composable business (move pieces around, connect pathways, simplify, or build out in response to market pressure or changing environments)
Past data models required lots of lead time to build the architecture and deploy. And once that happened, no one wanted to change things around because it meant more time spent within the build and less time getting insight. Companies received "just enough" insight to make forecasts based on the past, but left money on the table when it came to real-time decisions. Now, with the composable business model and a Data Fabric in-place, it's time for significant digital transformation.
Achieving Security and Self-service
Companies need to protect their data while providing flexible access to different teams and members. Data Fabrics provide companies with the governance they need (right down to the granular level) to protect data as their most valuable asset without tying up IT resources.
Imagine what departments can accomplish with data at their fingertips. The platform becomes collaborative with teams such as marketing, sales, IT, and product design—all on the same page, creating and innovating the company's next big thing!
A Data Fabric makes silos a thing of the past. It turns data of all shapes, forms, and volumes into real-time insight for all users, effectively turning even large enterprises into agile organizations that disrupt the status quo.
The Modern DataOS® mission is to dramatically change how companies do data...without the upheaval that often goes along with that change. DataOS transforms data in a matter of weeks without the need for disruptive retraining, massive downtime, or letting go of current solutions. Finally, data works for organizations instead of the other way around.
To find out more about DataOS features and how it can help your company build next generation data tools, download the Modern DataOS Overview.
