Organizations are undergoing a significant shift in their use of data. Many are looking for new data sources that can provide a more complete picture and inform analysis to deliver a tangible, transformative impact. Many organizations run on SAP and have found that SAP holds a lot of useful business data, but most large organizations have dozens of other systems with useful (often unused) business data.
Insights that can be gleaned from mining different new data sets can prove invaluable – particularly when existing data sets don’t reflect new or changing circumstances. For example, City Plumbing, a plumbing and heating company and part of Travis Perkins group in the UK, integrated historical industry sales data with its own sales information to create a predictive forecast that helped them navigate the new pandemic business environment. However, accessing and integrating data manually in these different systems can take up to 70% of the time estimated for an analytics project and often requires skills which are in short supply.
In fact, our research with IDC revealed that in 2020, 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. In order to pull all that data together, an integration tool like Qlik Data Integration (QDI) is the best way to replicate the data from SAP and other sources to cloud platforms such as Microsoft Azure.
Data Integration Challenges
However, 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 today’s agile business environment. These traditional methods are time-intensive, costly and often error-prone. Also while many companies are often more adept at integrating data from the cloud, they still 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 Tools That Fit Business Needs
Companies need integration solutions that keep pace with their business by automating and streamlining the integration process. The right integration tools can be transformative for a company, 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.
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 automate tasks associated with ingesting, replicating, and synchronizing data across the enterprise. This means that – often for the first time in their operations – 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. 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.
Getting The Complete Picture
Data integration doesn’t have to be a headache. The right solutions can simplify and automate the process, allowing 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 from SAP, on-premise or multiple databases eliminates human-error and time-intensive manual integration, giving a business the agility to respond quickly to real-time insights. Using modern and automated data integration technology solutions and techniques, organizations can reduce data integration costs by up to a third and halve the time it takes to get to useful insights from data. 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.
This article is sponsored by Qlik
