How to Connect Disparate Data Sources Into One Holistic View
In the age of digital technologies, modern businesses depend entirely on their ability to gather, process, interpret, analyze and store data.
The best course of action is to develop a single data source for all enterprise analytics to allow modern organizations to achieve greater data quality and consistency across all their data sources, no matter where they are stored.
Enterprises are now facing a big challenge – finding the best ways to increase the accuracy of their insights, regardless of who is in charge of analysis. Even the most average business is required to work with countless different data sources, and there is an ever-increasing need to integrate their disparate data sources.
That all leads us to conclude that many businesses are struggling to connect and integrate their disparate data into a unified solution that would provide them with countless new opportunities and advantages.
Fortunately, the following data integration practices might just be the solution your business needs to create a unified source of the most accurate, up-to-date insights.
Taking a holistic approach
The complexity and uniqueness of each niche analytical need and different data sources within one business enterprise make it quite challenging for many to make their strategy for data integration a reality.
That’s simply due to many obstacles that tend to get in their way:
- The trouble with aligning their existing analytics solutions with their current quality of data sources;
- Compatibility issues when trying to make their data warehouses compatible with particular data integration solutions;
- Taking non-comprehensive data integration approaches that hamstring their reporting capabilities.
One of the easiest ways to solve these problems is to shape your reporting capabilities to match your desired data sources rather than specific technologies. Let’s say that your goal is to increase your conversions by attracting qualified prospects and converting them into loyal customers.
That would mean that you need to consolidate your disparate data sources into advanced reports to help analyze the prospect journey and improve your lead generation strategies. To achieve that goal, you’ll need a practical, interactive data pipeline to transfer the data to the target cloud data sources, where you can transform the data into a unified format.
From there, you’ll need a business intelligence tool to create dashboards that would allow you to obtain actionable insights by performing data queries on a larger scale. A managed Presto is an excellent tool for achieving such a goal with minimal data losses.
Consider creating a manageable scope
Data integration is a pretty sophisticated and sensitive process, especially if it’s an enterprise-grade integration. Many companies wrongly confuse the single source of insights with a fully-formed, enterprise-wide scope of data repository needs. Because of that, their end-to-end data integration processes take forever before they start seeing any direct ROI.
If your business needs a more rapid solution for receiving ROI, you’ll need a more efficient data integration strategy that would:
- Map your entire data ecosystem;
- Connect disparate data sources into a centralized, unified platform;
- Take care of advanced reporting by creating essential dashboards;
- Implement advanced data science and analytics capabilities.
If you want to provide a more rapid ROI, you’ll need to shift focus to mission-critical components that allow you to do so. More importantly, you’ll also need to think about scaling up the depth of your analytics to match the new breadth of your target data systems. This approach can benefit your operations in two ways:
- You’ll be able to test the accessibility and functionality of your data systems in real-time to make all the necessary adjustments and enhancements before you start scaling your operations;
- You’ll be able to develop clear and strong use cases before the scaling begins, making collecting buy-in from across your team much easier.
Find a perfect business intelligence tool for connecting disparate data sources
Transforming your dispersed data warehouses and silos to a centralized data platform isn’t something that can happen overnight. It’s a massive change for your organization that is simply monumental to your business operations.
That is why every modern enterprise organization needs a perfect business intelligence tool to foster all your data integration needs and ensure your new centralized system is as comprehensive and accurate as expected.
Such a tool can communicate the real values of your unified data systems to different end-users. It can empower them to abandon traditional systems and accept more efficient solutions while following the latest data quality practices and maintaining the highest level of accuracy of data enterprise-wide.
Again, that’s where managed Presto can help. It has many analytical use cases and it also excels at ad hoc and interactive querying. Some of the most common Presto use cases include:
- Interactive analytics – Presto allows you to tap into a wide range of BI tools, notebooks, dashboards, and visualizations to conduct multiple queries and quickly analyze disparate data sources;
- Batch ETL – achieve better efficiency and throughput for processing and integrating data in the warehouse/silos;
- App analytics – create a centralized platform for deploying multiple highly concurrent queries and developing external-facing, low-latency customer reporting;
- Ad hoc querying – Presto is an SQL query engine with multiple connectors that can run ad hoc queries wherever, whenever, regardless of where the data is stored and without the need to ETL data into separate query engines/systems;
- Reporting and dashboarding – connect disparate data from multiple sources to build one holistic view of dashboards and reports and get all your business intelligence under one roof;
- ETL queries – connecting disparate data sources with success depends on your ability to gather petabytes of data across multiple data sources. Presto allows you to conduct efficient, high-throughput ETL queries against all your target data sources;
- Data lake analytics – save time, effort, and resources by querying structured and unstructured data directly on data lakes, thus eliminating the need for transformation.
As you can see, connecting disparate data sources into one holistic solution is much simpler with the right tool in your hands than many companies want to believe. However, the trick is to build your business intelligence solution around your unique data needs rather than locking yourself in the technology needed for achieving your data goals.
If you shift your focus to your data integrating capabilities instead of specific technologies, you’ll easily achieve your data integrating goals without disrupting any ongoing business processes. The result will be a centralized view of all your data, increased customer/employee satisfaction, and increased ROI, among many other things.