An enterprise data warehouse (EDW) or data warehouse is a technological solution used by a company to centralise, store, analyse, and transform its data.
The fundamental objective of EDW is to keep the information in a manner that speeds up and advances business analytics that precedes insights for the business and competitive intelligence.
Why Do Companies Need an EDW?
Companies traditionally stored their records in relational, well-organised, and high-structured databases. Yet, as technology advances, relational databases weren’t able to adjust to the increase in data.
Databases had several issues in each of the following: volume, speed, data type, and different external sources of data.
- Volume – database can hold a huge amount of incoming data so long that the data observes ACID constraints. Vast parallel data entries and replicated records impose a challenge to the traditional type of databases.
Unless invested upfront with a lot of engineering customisation, relational databases are not boosted to hold distributed incoming and duplication transformation without incurring performance costs.
- Speed – conventional databases were quick at inserting information but decelerated in typical analytical inquiries, which demands a lot of transformations.
- Data Types – conventional SQL databases were not prepared to increase NoSQL information like IoT logs, geographic data, graphs, and the like.
- Different External Sources of Data – businesses are troubled with additional issues trying to match and model their information within databases. The process of ETL or Extract- Transform- Load is vital for both EDWs and DBs.
These urged a technological revolution that has given birth to EDWs.
The Advantages of Using EDWs
- Faster Insights – By relying on a structure designed with analytics kept in mind, enterprise data warehouse users get to access faster insights.
Inquiries that took hours or days are shortened to minutes or seconds. As a result, analysts can redo the data quicker and identify new opportunities for business progress.
- Data Centralisation – EDWs merge information access through the different networks of data sources and repositories. This provides a complete view of various business silos and shuts the gap between different business ventures.
- Simplified Operations – EDWs are part of ETL operation, which extracts data from its raw form (extract), transforms it (transform), and stores it (load) on the database or data warehouse where it should be.
EDWs offer tools and integrations to different software that automates features of the ETL (extract-transform-load) for faster provision of usable data.
- Data Security and Reliability – the best EDWs offer several layers of security to maintain your data from peeping eyes. Along with data encryption and reliability considerations, EDWs do the hard work in the matter of keeping your information secure and operating QA or quality assurance checks.
To make the transitions easy from databases to business data warehouses, here is a simple four-step procedure for guidance:
- Make a list of EDW providers centred on the assessment criteria listed above.
- Determine whether you want to move your existing information to the new platform of EDW or you want to start afresh.
- Identify success criteria.
- Establish a proof of concept from each of the shortlisted vendors and compare them to the success criteria.
Getting started with an enterprise data warehouse can somehow be intimidating, but with the right knowledge and resources, it should be easier to accomplish.
