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What Causes Information Gaps? 3 Challenges Companies Face

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Information Gaps usually boil down to three challenges that organizations wrestle with when it comes to data: Implementation challenges, synchronization challenges, and data culture challenges. If any one of these exist, there’s likely a gap between the data that an enterprise has and the information that teams need to realize transformational business value.


The Implementation Challenge


What causes it?


The Three D’s generate more data; but more critically, they generate more work for data teams. These teams need to get pipelines from experimentation to production faster. They need to quickly and easily reuse common architecture patterns or pieces of code so that each project builds on the foundation of the last. They need to take input, perform business logic reviews, and incorporate subject matter expertise from all areas of the organization. And they need to combine elements of data science and traditional analytics engineering to deliver mix-mode projects at speed and scale.


If the team attacking this challenge is small and relies on hand-coding to get the job done? They’re sunk, and the Information Gap widens. It also doesn’t help that data engineering and data science teams often have different timelines and different agendas, work in different parts of the cloud, and deal with different data types (structured data vs. semi-structured and unstructured data). 


The result


If it takes a week or more to even prepare data for analytics, and weeks or months to build the models that yield information, it’s impossible for enterprises to quickly make insight-based decisions, create personalized experiences for customers, or rapidly deploy new products in the marketplace. Given the speed of business today and the expectations of customers, implementation challenges can render a company irrelevant in a short period of time.


The Synchronization Challenge


What causes it?


Traditionally, data teams prepared and analyzed data that most often ended up in business dashboards for a few stakeholders to interpret and act on. The days of the dashboard as the final resting place for information are over. Enriched data and insights need to go beyond the static dashboard and into the heart of the business, where they are accessible to all. 


Data teams need to treat their data as a continuously recirculating asset and make it available to drive automation in the tools and processes that run their daily operations. IDC predicts that the most data-forward organizations will adopt “headless analytics” by 2025 (1). 


But moving that information back into operational systems, data models, and new products can be complicated and time-consuming for data teams who lack the right tools. 

The result


If information can only be seen by a few, it can’t affect change where it needs to happen: On the front lines of the business. End users can’t use it to score leads, decide on next best actions, surprise and delight customers, or plan content and campaigns that will move the needle for the enterprise. 


The Data Culture Challenge


What causes it?


As the strategic value of data and analytics increases in an organization, so does the need to make it accessible to those who can transform it into useful information. However, legacy tool sets were not built with democratization in mind; they exist for specialized operators who endured hundred-hour training courses and years of hands-on experience to gain full mastery. 


That won’t cut it at an enterprise that needs to move faster, and where data-savvy workers that are a part of “Gen-D” want to manipulate the data themselves. Data teams need to enable these users to work with data in a controlled and curated environment and champion statistical best practices.


The result


Unfortunately, data teams relying on legacy technology can never truly sustain the culture needed to create a truly data-driven organization. And as Gen-D workers continue to bypass the best practices of curated analytics, information gaps continue to flourish in unsanctioned reports across the business.


Closing the Information Gap


If your organization has an Information Gap, how do you close it? By enabling shared, secured, and connected data throughout the organization, facilitated by cloud data platforms, cloud-native tools, and processes that facilitate collaboration and data-driven operations. 


Improving implementation


  • Align your data teams and empower them to work together with shared data and shared tools. 
  • Decrease the learning curve and make it easier to onboard new data team members with highly visual, easily understood tools that provide a simplified way to work with complex logic. For example, low-code/no-code ELT software can streamline and automate many of the steps involved in integrating and transforming data and put valuable skills into the hands of many instead of a few. 
  • Choose tools that enable asynchronous collaboration with auto-documentation, real-time shared workflows, and support for Git and other platforms. 


Synchronizing data across the business


  • Think beyond the dashboard and send enriched data back out into operational systems where end users can make more informed decisions on the front lines. 
  • Investing in a cloud data platform such as a lakehouse or a data cloud that enables teams to work with data in both structured warehouses and unstructured environments like a data lake can help ensure that teams are working from the same enriched, prepared, analytics-ready data. 
  • Move away from data pipelines to data lifecycle management, with data flowing in and around the organization and constantly evolving.
  • Choose data integration tools that re-integrate enriched data back into operational systems via two-way connectors. 

Promoting a true data culture


  • Instill data best practices throughout the organization with everyone from technical teams to executives to data end users. 
  • Establish data governance that doesn’t restrict data, but instead enables secure access for people who need it, as well as clear data lineage. 
  • Create shared environments where everyone on your team can work from their preferred interface and toolsets while all using the same datasets


Learn more about closing your Information Gaps


Want to learn more about how to overcome and close Information Gaps in your organization? Download our latest ebook, Close the Information Gap: How to Succeed at Analytics in the Cloud.


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(1) IDC Futurescape 2021