What is Data Warehouse?

Nowadays, when you download any mobile application, they first ask you to register using your email address and then ask you to give it permission to access your data. Once you give them all the permissions, you can get a personalized experience on the platform. But why are companies hungry for customer data, anyway? Well, collecting more and more information about all the customers allows companies to understand their buying preferences, and then make more informed decisions on how to improve their products and services. Apart from customer data, gathering business data related to supply chain, sales, shipping information, availability of products, vendor details, and more also helps in knowing the current state of the business and aid the next steps to be taken. All these steps come under the technical term known as Business Intelligence (BI). 

Business Intelligence involves the utilization of advanced tools and techniques to transform business data into actionable insights, i.e. uncovering hidden trends and patterns that would usually go unnoticed by the stakeholders. Getting the final reports, graphs, and dashboards that reveal the crucial correlations involves a whole lot of complex steps performed on the raw data – collection, cleaning, modeling, processing, and analysis. 

Now the data that is to be collected comes from heterogeneous sources and may be structured, semi-structured, or unstructured. These sources can include data from social media platforms, IoT devices, logs from web servers, transactional systems, and data streamed from online business applications using APIs. So, the first step companies usually take to gather data in one place is that they create a data warehouse. We can simply consider a data warehouse as a central repository of business data from where the BI tools can quickly access it to convert the information into meaningful insights. 

Are you a data geek or someone willing to start a career in data science? If yes, then it becomes inevitable to know about data warehousing. Being an important concept, data warehousing is covered in all the reputed data science training programs people take to build a strong foundation in this domain. This article helps you gain a complete overview of what data warehouse is all about.  

What is a Data Warehouse?

As already mentioned, data warehousing is the process of gathering and maintaining large datasets generated from various disparate sources. Designed to support business intelligence activities, a data warehouse is different from a regular operational database. A standard database is used for multiple transactional purposes and made to record and retrieve information in real-time. On the other hand, a data warehouse collects data from such databases, stores the information over time, and is used to make large data sets easier for analysis so as to discover patterns and relationships. 

Various advanced data warehousing tools are available in the market today. These tools first help in collecting data from multiple sources. As the incoming data may not be properly structured, the next step involves cleaning the data to eliminate any kind of errors or duplicate entries. Also, data from all the sources may not be in a single format, so the data needs to be converted from their initial format to a warehouse format. When the data is available in the accepted format, it is then sorted, consolidated, partitioned, and checked for integrity. Finally, the data is updated from time to time to make it ready for analysis.    

Benefits of Data Warehousing

The practice of data warehousing is being adopted by various industrial sectors, like healthcare, banking and finance, aviation, retail, and telecommunications. Here are some of the benefits that these sectors are reaping by adopting this centralized data storage system.

  • Companies get improved access to information and business leaders can make data-driven decisions as data warehousing allows effective data analysis and reporting.
  • Data warehouse helps in revealing the current state of the business processes. When the historical data is cleaned and analyzed, stakeholders can understand what processes can be improved to deliver faster results. 
  • The better the decisions taken by the stakeholders due to data warehousing, the higher will be the revenue generation. 
  • Today’s data warehouses are cloud-based and thus offer scalability so that they can handle even more queries as the business grows. 
  • As the data from various sources is converted into a standardized format, each team using it can produce results that are in line with the teams of other departments. 

With such benefits, companies like Microsoft, Amazon, and Google have integrated data warehousing with their cloud services. Amazon Web Services (AWS) offers Amazon Redshift, Microsoft Azure offers Synapse Analytics and Apache Hive on HDInsight, and Google Cloud offers BigQuery service for data warehousing solutions.   

Learn Data Warehousing

Data Warehousing is often used as a part of the data science process, and if you are seeking a data-related job role, you will be expected to be familiar with it. Many professionals prefer taking a comprehensive data science online course so as to learn data warehousing along with the other important concepts. As cloud service providers are offering data warehousing services, it has become even easier for companies to adopt it and leverage its potential. Since there is no infrastructure required with cloud-based data warehousing, companies can jump-start data analysis cost-effectively and accelerate their digital transformation journey with ease. So, why not gain data warehousing skills and improve your career prospects in data science.

You may start with an aws certification path course to give you more context on data warehousing.

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