Are you trying to know the benefits of data warehouse?
This guide is for you.
Data warehouse helps to reduce total turnaround time for analysis and reporting.
Restructuring and Integration make it easier for the user to use for reporting and analysis. Data warehouse allows users to access critical data from the number of sources in a single place.
Often big companies invest large sums of money on data warehousing tools and technologies so that they get up-to-date, accurate, and integrate information about their products and customers. A Data warehouse (DW or DWH) is a database used for reporting and data analysis.
A data warehouse usually contains historical data that is derived from transaction data. And the main purpose of it is to improve data quality and provide a coherent picture of the business at a point in time.
In this context, we shall look into the Advantages of Data Warehouse along with what Data Warehouse testing is.
Some benefits of Data Warehouse
A data warehouse, once implemented into our business intelligence framework, can benefit the company in numerous ways.
Following are some advantages of Data Warehouse:
1. Delivers enhanced business intelligence
Having access to information from various sources from a single platform. And decision-makers will no longer need to rely on less data or their instinct. In addition, we can effortlessly apply data warehouses to a business’s processes.
2. Saves time
A data warehouse standardizes, preserves, and stores data from distinct sources, aiding the consolidation and integration of all the data. Since critical data is available to all users, it allows them to make decisions on key aspects faster.
3. Enhances data quality and consistency
A data warehouse converts data from multiple sources into a consistent format. However, the data from across the organization is standardized such that each department will produce results that are consistent.
4. Generates a high Return on Investment (ROI)
Companies experience higher revenues and cost savings than those which don’t have a data warehouse.
5. Provides a competitive advantage
Data warehouses help get a holistic view of their current standing and evaluate opportunities and risks. Above all, it provides companies with a competitive advantage.
6. Improves the decision-making process
Data warehousing provides better insights to decision-makers by maintaining a cohesive database of current and historical data. similarly transforming data into purposeful information, decision-makers can perform more functional, precise, and reliable analyses and create more useful reports with ease.
7. Enables organizations to forecast with confidence
Data professionals can analyze business data to make market forecasts, identify potential KPIs, and gauge predicted results, allowing key personnel to plan accordingly.
8. Streamlines the flow of information
Data warehousing facilitates the flow of information through a network connecting all related or non-related parties.
What is a Data warehouse testing
It is the testing of the data warehouse to verify whether the data transforms correctly according to various business requirements and rules, to ensure to load all the data correctly into the Data warehouse without any data loss and truncation.
Moreover, it involves checking the loading of data into the data warehouse in the expected time to ensure performance.
Data Warehousing Testing is also known as ETL Testing (Extract, Transform and Load).
What are the challenges in Data warehouse testing ?
Data warehouse testing is quite different from traditional testing methods.
The following are some of the challenges:
1. Firstly, having very little Testing Tool for the test
2. Automated Testing is not always possible
3. Data traceability not always available.
4. And it requires extensive functional knowledge
5. Furthermore, it deals with bulk data
6. Some times we will have to handle incompatible and duplicate data
7. The chance of losing data during the ETL process is more
8. There are no privileges for the testers to execute ETL jobs on their own
9. Volume and complexity of data is very huge
10. Missing business flow information will result in inefficient testing