Solving data integration challenges by using data warehouse automation

When it comes to data warehouses, the collected data can be stored in a number of different forms. In order to effectively analyse and use the data, data enterprises often need to integrate the information to make it compatible. This takes a lot of manual work, which, in turn, can take up valuable time. To combat this, data automation tools can be used to streamline the process. Here we examine why they’re so valuable for organisations.

As data warehouses store data in a variety different forms, this can cause problems for data enterprises and controllers trying to effectively analyse the data they have. Integration is the process of translating all data into one, unified form. The process involves correcting discrepancies in naming and units of measurement. This enables organisations to analyse the data more efficiently, drawing results that they can use effectively.

Data integration done manually can often go awry for a number of reasons, including:

  • Incorrect information entered into the source system
  • Inadequate knowledge of interdependencies among data sources
  • Differing timelines amongst data sources
  • A data warehouse system that is overly complex
  • Approximations used in data
  • Different encoding formats
  • Overall lack of policy and planning within the data enterprise

Data warehouse automation goes some way to addressing these issues. But what exactly is automation and how can it help?

Data warehouse automation is described by The Data Warehouse Institution as ‘using technology to gain efficiencies and improve effectiveness in data warehousing processes’. They argue that ‘data warehouse automation is much more than simply automating the development process’. In their eyes ‘it encompasses all of the core processes of data warehousing including design, development, testing, deployment, operations, impact analysis, and change management’.

In short, data automation lets you do far more in much less time, making it an invaluable tool for all organisations that have data warehouses. The benefits include:

  • Quality – Automated processes allow you to control and maintain integration quality across the board. It can essentially eliminate human error which can lead to the discrepancies lists above.
  • Agility – Business requirements can often change at a rapid pace. While manual integration might not be able to keep up with this, automation can.
  • Cost – Automation can reduce an organisation’s costs. Reducing the amount of manual work involved means that IT specialists and data scientists can get on with other pressing jobs.

Understand more about how your business can utilise data warehouse automation techniques by attending Big Data LDN on 15-16 November 2017, registration is free!

Recent Posts


Big future for big data at Big Data LDN


Data projects delivered at cost deficit – how DataOps changes this


Accelerating People Analytics