In our last article, we talked about the importance of ETL for BI. This article introduces the concept of Real-time ETL and Data Warehousing and how they are revolutionizing Business Intelligence.

Traditional batch processing is being phased out and with the era of relational database era drawing to a close, businesses have turned to real-time data integration to automate business processes, operations and reduce the time taken to generate strategic insights across the organization. The increasing popularity of hybrid IT environments have also contributed to this decline of legacy ETL tools and data warehouse processes. The main goal is to connect every part of the business in a way that it works as a unit to generate the most current updates and information. Management and IT teams today want quick access to database changes as and when they happen, in other words, real-time updates. To keep up with the demands, ETL and Data Warehouses have evolved to the next stage – Real-time ETL and Data Warehousing.


What is Real-time ETL?

Businesses today are driven by the need to manage and store massive amounts of data without adversely impacting the time to insight since. Their competitive nature demands real-time data and databases powered by critical applications and purpose-built for business intelligence and analytics. Traditional ETL processes are finding it hard to keep up with the demands of a modern business.

ETL is responsible for detecting changes in data, extracting it to a staging area and transforming it to the right format before loading it into a data warehouse at periodic intervals. However, with global data warehouses on the rise powered by near-real time data sources, ETL has evolved to generate accurate analysis relevant to the current situation using real-time data. With this, the data warehouse is updated continuously, instead of periodically, after there is a change in the source data.

Features and Basic Architecture of Real time ETL

Traditional ETL architecture comprised a simple four-layer system – the data sources (for extraction), the Staging Area (transformation), the enterprise data warehouse (loading), and the end-user presentation and reporting tools.

Traditional ETL, ETL, DW, Data Warehouse

Real time or near real time ETL has the following elements:

  • Data sources, comprising a data store & DBMS or Database management system that are stored in the data warehouse
  • A temporary Data Processing Area (DPA) for transforming the data
  • The Global Data Warehouse where content is loaded and stored in continuous or near-real time feed

Changes in the sources are first scrutinized and identified by a Source Flow Regulator module as relevant for ETL and then moved to the warehouse. Another module – Data Processing Flow Regulator module – decides which source is ready yield data. The intermediate processing area receives the data where the ETL workflow acts to clean, profile, organize and transform the data after which it is loaded in the global warehouse where a Warehouse Flow Regulator oversees the feed from the Data Processing Area (DPA) to the warehouse based on factors like end user queries, ETL throughput, query response time and QoS “contracts.”

ETL, Real time ETL, DW, business intelligence

Benefits of Real time ETL and Data Warehousing

While there are challenges at each stage of the ETL process, on the whole, agile practices adopted by organizations, to harvest massive volumes of data, are driving the transition from traditional to real-time ETL. Organizations are continuously researching better approaches to ETL to keep up with the market trend of using only fresh information. Benefits of Real-time ETL and Data Warehousing include:

  1. Accuracy and timely flow of information in a data warehouse
  2. Real-time events and data are detected and extracted from applications and databases
  3. Since only the changes in data sources are processed regularly, it reduces the ETL run time
  4. A non-intrusive log-scraping technology reduces the impact on the source systems
  5. A CDC system integrated with ETL simplifies the development process
  6. Low-cost and low-budget without massive investment and recycling of existing investments
The Impact of Real time ETL and Data Warehousing on Business Intelligence

The growing demands for fresh information for analysis and Business Intelligence has given rise to the concept of real time or near real time ETL.

ETL is the first step in generating relevant and accurate insights that power corporate decisions in the form of business intelligence. An efficient ETL process results in accurate insight generation and an efficient real-time ETL process can dramatically improve business performance with timely and accurate, strategic insights.