Data warehouse to generate relevant analytics
A data warehouse is a key aspect of any business. It’s a place where
all the data of an enterprise is stored from heterogeneous sources so
all the analysis can be made on that data to derive key decisions or
form any strategy.
A data warehouse works as a central store
where information arrives from the integration of one or more data
sources. Data flows into a data warehouse from the transactional
system like CCTV camera and other relational databases like MySQL,
MongoDB, Neo4j etc. The data can be classified into: Structured like
employee information, inventory management, etc Semi-structured like
custom forms etc. Unstructured data like video recording, audio,
etc.The data is extracted, transformed, and loaded so that users can
access the processed data in the data warehouse through BI tools, SQL
clients, and spreadsheets. A data warehouse merges information coming
from different sources into one datastore. By combining all of this
information in one place, an organization can examine its customers
more holistically. This ensures that it has considered all the
information available. Data warehousing helps in making data mining
possible.
Types of Data Warehouses
Complete Analytics
Enterprise Data Warehouse is a centralized warehouse that provides decision support services across the enterprise. It offers a unified approach for organizing and representing data. It also provide the ability to classify data according to the subject and give access according to those divisions.
Operational Data Store
Operational Data Store, which is also called ODS, are nothing but data store required when neither Data warehouse nor OLTP systems support organizations reporting needs. In ODS, Data warehouse is refreshed in real-time. Therefore, it is widely preferred for routine activities like storing records of the employees.
Data Mart
A data mart is a subdivision of the data warehouse. It is designed for a particular line of business, such as sales, or finance. In an independent data mart, the collection of data can be done directly from sources.
Outcomes
Enhanced Data Quality and Consistency: Implementation of a data warehouse includes the conversion of data from numerous source systems and data files into a standard format. As each data is centralized from various departments, each department produces results that are in line with other departments. This brings accuracy, quality, and consistency in data.
Enhanced Business Intelligence: Merging data from multiple data sources is a common need when conducting business intelligence. For solving this problem, the data warehouse performs the integration of existing data sources and makes them accessible in one place.
Timely Access To Data: The data warehouse enables decision-makers and business users to have access to data from many different sources as they need to have access to the data.