Integrating New Data Sources Without Muddying The Water

Organizations are undergoing a significant shift in their use of data. With the current situation unlike any that businesses have operated in before, many are looking for new data sources that can provide a more complete picture and inform analysis to deliver tangible, transformative impact.

In fact, our research with IDC revealed that over the last 12-18 months, over two-fifths of US business leaders reported that their organization had introduced new external data (40%), new internal data (45%) and new data types (45%). The study also showed that more source data is in more disparate locations: on multiple cloud platforms, on-premises, and at the edge.

Insights that can be gleaned from mining different data sets can prove invaluable – particularly when existing data sets don’t reflect new or changing circumstances. City Plumbing, a plumbing and heating company and part of Travis Perkins group, for example, integrated past industry data from recessions that resulted in similar collapses in sales, with its own data to help them navigate the pandemic. This helped them predict how demand would change and equipped them with insights that inform decision-making around sales and forecasting.

Data Integration Challenges

But, the process of extracting, transforming and consolidating disparate data sources is not without its challenges. Traditional data integration processes, such as manually extracting, transforming and loading data (ETL), are proving unfit for purpose in today’s agile business environment. These methods are time-intensive, costly and often error-prone. Companies are often more adept at integrating data from the cloud, but need to ensure that they are mining all sources to gain a complete picture. Pulling data from on-premise, mainframes, SAP, various databases, or even alternative cloud sources often involves heavy coding and deep scripting, leaving skilled workers investing time in manual integration when their expertise could be better utilized elsewhere in the business.

Finding A Tool To Fit Business Needs

Companies need a solution that keeps up with the pace of business by automating and streamlining the integration process. The right integration tool can be transformative for a business, enabling them to take advantage of diverse and disparate data to support the bottom line. These include:

  • Avoiding cloud lock-in: Organizations need to ensure they’re not locking themselves into a single-cloud vendor. When new data needs capturing, it is important that the selected tool can integrate data from new sources quickly and effectively. A platform that uses automation in the context of Change Data Capture (CDC) enables data from all different sources to be replicated and streamed, as and when changes occur, for near real-time analysis. This gives the business agility to respond quickly to new data and ensures that they can host and analyze it in an optimal cloud platform.
  • Removing the risk of human error: Modern data integration tools can automate the integration process, removing human error, connecting data sources faster and more effectively. Modern tools can automate tasks associated with ingesting, replicating and synchronizing data across the enterprise. They can also switch the process of ETL to ELT to deliver real-time data for analytics or machine learning projects. This means that – often for the first time – analysts have comprehensive, instant data insights without the risk of incorrect data making its way into the pipeline.
  • Real-time integration: Automating ELT also offers businesses the ability to integrate data in real-time – across on-premise and cloud environments – into one target. By integrating insights immediately, businesses can ensure they have one single version of the truth across the business.

Getting The Complete Picture

Data integration shouldn’t have to be a headache. The right tool can simplify and automate the process and allow businesses to focus on the insights that inform decisions, rather than concentrating on how to get them to the right place. Automating the integration process eliminates human-error and time-intensive manual integration, giving a business the agility to respond quickly to real-time insights. By creating a single version of truth through organization-wide automation, businesses can ensure every team member is equipped with a complete, comprehensive picture to inform decision-making and improve business outcomes.

Per @AdamMayerwrk - #data integration doesn't have to be a headache; the right integration tool can be easy to use & transformative for a business

 

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