Overview
The term ‘Data’ is so widely and commonly used that we take it for granted. Have you ever given a thought to where is this huge amount of data stored? For example, let’s consider some large organizations such as Meta or Google. How do these Big O’s manage large data daily? How do they make sense out of it? And the main important question- How do they even manage to transform this huge raw data into meaningful insights that drive various decisions? Worry not, In this article, we will answer the following questions:
- What is a data warehouse?
- What is the purpose of data warehouse?
- What are the benefits of using a data warehouse?
- How does a data warehouse impact analytics?
- What are the different usages of data warehouses?
Mark my words and you will have a clear understanding of data warehouse, by the end of this article!
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Definition
In very simpler terms, a Data warehouse is a storage system that connects and stores large amount of data from multiple different sources. Data warehouses are designed in such a way that they can handle raw, structured or unstructured data like videos, image files from multiple sources such as Point-of-Sales transactions, Marketing, CRM, IoT and more. Data warehouses usually stores both current and historical data in one place and will act as a single source of truth for the consumer. Its purpose? To provide a centralized storage space for all the data required to support reporting, analysis, and other business intelligence functions. This allows companies to make smart decisions using data. I bet you’re already thinking, “Wow, the concept of a Data Warehouse isn’t that tough to grasp! It is a type of database that stores information to satisfy decision-making requests.”
Benefits of Data warehousing
A data warehouse that is designed well is the foundation for any successful BI or analytics programme. This further allows businesses to run reports, create dashboards and use analytical tools that have become almost common today. There are many benefits of using Data warehouse, here I’m listing just the top ones:
Data warehouse allow you to quickly pull data from multiple sources into one location so that one can perform analysis. While loading data, it is cleaned and processed which ensures data is stored in a consistent format guaranteeing accurate and high quality data.
The key benefit of building data warehouse is to have fast data retrieval. You will rapidly get results by querying on large amount of consolidated data with little or even no support from IT.
DW has had a significant impact on analytics. As we have access to historical data, DW makes possible the analysis for past trends, challenges and patterns to make future predictions. By having access to real-time and past data, DW allows for more accurate reporting, forecasting additionally supporting predictive analytics. It provides an excellent foundation for advanced analytics techniques like ML and AI.
We all know how fast the data is growing. And as your business grows so will be your data. Data warehouses can expand to accommodate these increasing data volumes.
Different Usages of Data warehouses
Almost all the major organisations across the globe use data warehouses for their operations. I will cite a few examples from different industries to help you understand the practical applications.
As you may have read above, the primary use of DW is to lay the foundation and support the Business Intelligence activities. Data from DW powers creation of interactive dashboards to provide real-time information. Not to forget the C-level executives often rely on the reports of company performance build on the data from data warehouses. I’m sure you may have come across or seen the beautiful dashboards that were created as part of Coca-Cola project. The dashboards were used to track the sales performance, to examine the market share and consumer preferences across the global markets.
We all know how Netflix analyzes our viewing habits and then sneaks in recommendation per our personalized content. DW plays a major role in it, improving customer satisfaction and mainly retention. How does DW works in this case is by enhancing CRM. It helps Netflix analyze customer data in DW that comes from different regions to create targeted marketing campaigns and thereby identify customers at risk of leaving.
DW plays a very crucial role for all the industries in financial sector. The historical data is used to evaluate the risks when making lending decisions. American Express (AmEx) leverages the date from DW to detect in fraudulent transactions in real time. Similarly, we often get a call from our bank if we do any transaction that is categorized as unusual. This all happens in real time using the data from DW thereby protecting customers from fraud and reducing financial losses.
There are so many usages I can mention in Healthcare industry that utilizes data warehouse to analyze patient data to identify the most effective therapies. Human Resources is another application where DW is leveraged to forecast staffing needs or tracking employee performance. The organization in Scientific and Research need massive data warehouse to store and analyze data from their experiments. The scientists often rely on large datasets to track changes, trends and patterns over extended periods of time.
In Summary
Today, the Modern data warehouses and increasingly the cloud data warehouses are a key part of success for the companies and their business units. DW allows them to capitalize on their business needs by combining data from multiple sources with new and important information. DW’s provide fast data retrieval and allows complex data mining without any disruption in performance of other business systems. Datawarehouse is nothing short of a power house that allows companies to utilize full potential of their data. Regardless of you being a student, working professional or business leader having understanding of data warehouse is key in navigating your career.
Useful Link – Data Analytics Certification Training | Top 12 Data Analytics Tools in 2024
