This is the first of our three-part series on the Future of Data Integration. The article talks about the important role ETL has played in obtaining relevant business insights and intelligence.
ETL and Business Intelligence
For a business to make profitable and valuable decisions, it needs access to relevant business intelligence (BI) or analytics that drive informed decision making for the company. These insights are derived from data or to be more specific, data that is converted into meaningful, actionable information. This information is extracted and accessed by BI tools and applications and subsequently end-users and analyzed to generate the required insights. Here lies the work of ETL or Extract, Transform and Load. It is a data integration process which extracts the raw data from the respective source systems, transforms it into ‘information’ and loads it into a data warehouse or repository where it is ready to be used by BI and reporting tools for analysis.
A Three Step Data Integration Process
The basic ETL process is the same across all tools – it extracts, transforms and transfers data from source to the destination data warehouse. ETL comprises three steps:
Extract – Raw or native data is pulled from different source systems like ERPs, Applications, Cloud, Operating systems etc. and converted into a single data warehouse format ready to be transformed.
Transform – Business rules are applied to the data which is cleaned, mapped, filtered, split, merged, transposed, or validated and standardized into schemas or formats.
Load – The transformed ‘data’ is transferred or ‘loaded’ into a data warehouse (storage), ready to be accessed by reporting and other tools.
The Relevance of ETL and moving beyond traditional ETL
As a data integration process, ETL has been around for a long time. But it is not a new concept in IT, it has evolved over time and with the advent of big data analytics, reinvented itself. A business comprises numerous departments, each of which uses and stores data differently. Modern ETL tools help to integrate scattered, unstructured, and native data into a consolidated format which is processed and stored as ‘information’ in a single data warehouse. This information is easily accessible by the end-users or individual departments.
Today ETL tools and processes are used by some companies as a structured solution for delivering relevant business insights for businesses with powerful financial reporting requirements. It allows an enterprise to quickly access relevant, critical information from a single repository – the data warehouse and process it for analytics.
However, in the war of businesses, the power lies with the ones that can effectively utilize their data to move ahead in the game and we need to look beyond traditional ETL tools and find better means to quickly extracting and processing strategic information.
Look out for our next article on real-time ETL and Data Warehousing. Please contact us for more information on our data integration solutions.