Data Consolidation: Overview & Techniques

By |2020-07-15T08:12:27+00:00July 15th, 2020|

To the external world, your organization may appear as a highly systematized structure. But internally, it is a hodgepodge of data gathered from databases, files, and several other sources. This data can help your business evolve and improve, but only if you manage it efficiently. And data consolidation can help you do that!

In this blog, we’ll present an overview of data consolidation and some common data integration techniques used for consolidating data.

What is Data Consolidation?

In every business, data is produced from a range of sources and in various formats. Data consolidation is the process that amalgamates all that data, eliminates redundancies, and removes inaccuracies before storing it in a single location, such as a data warehouse or database.

Consolidating data enables companies to efficiently plan, implement, and execute business processes and disaster recovery solutions. This is because presence of all critical data in one place grants users a 360-degree view of all their business assets. This eliminates chances of errors, fast-tracks process execution, and simplifies information access.

Data Consolidation Techniques

The following are the three most common data consolidation techniques:

ETL (Extract, Transform, Load)

ETL is one of the most widely used data management techniques for consolidating data. It is a process in which data is extracted from a source system and loaded into a target system after transformation (which may include data cleansing, aggregation, sorting, etc.).

ETL can be carried out in two ways:

  • Batch processing: It is suitable for running repetitive, high-volume data jobs.
  • Real-time ETL: It uses CDC (Change Data Capture) to transfer updated data to the target system in real-time.
data consolidation techniques

Source: Wisatakuliner

Data Virtualization

Data virtualization integrates data from heterogeneous data sources without replicating or moving it. It provides data operators with a consolidated, virtual view of information.

Unlike the ETL process, the data stays in its place but can be retrieved virtually by front-end solutions like applications, dashboards, and portals without knowing its specific storage site.

Data Warehousing

Data warehousing is the process of integrating data from disparate sources and multiple locations, and storing it in a central repository to facilitate reporting, business intelligence, and ad-hoc queries. It provides a broad, integrated view of all data assets, with relevant data clustered together.

With data gathered in a single place, it becomes easier to determine trends and create business plans accordingly.

data integration

Wrap Up

The data consolidation tasks offer businesses a number of benefits. When data is stored in one location, it requires a smaller setup for management. This allows businesses to cut down their costs. Simultaneously, by consolidating data, you can enjoy better control as there are fewer processes involved in data retrieval and you can access data directly from one place. This ensures significant time savings. Plus, planning, implementing, and executing disaster recovery solutions become comparatively easier as all the critical data is in one location.

If you’re looking for an easy-to-use, user-friendly solution for consolidating data, give Astera Centerprise a try! The software offers users the option to consolidate data using ETL, data virtualization, or data warehousing. You can select the technique that best fits your requirements.