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Data Lake Vs. Data Warehouse: What Is The Difference?

Data Lake Vs. Data Warehouse: What Is The Difference?

At present data remains one of the key aspects of innovative technologies, and just like any of them needs to be protected, stored, and appropriately managed to provide you with the best experiences. Needless to mention, effective and reasonable data utilization can in fact bring various profitable benefits to different kinds of businesses. 

This article covers the two different concepts for big data storage and processing: data warehouse and data lake. Additionally, you€™ll be able to discover their main benefits and purposes of choosing the right option for your business. 

Data Warehouse: Definition, Features and Practical Employment

A data warehouse is a system used for enabling and supporting various business activities, related to big data analysis and structuring. As a rule, the reports got from the data warehouse systems are used for analytical intentions, business strategy development, and improving or reporting purposes. Because of employing real-time data analysis, the system can provide the most updated information that can be easily employed in any business aspect. 

The basic features of the data warehouse system include reporting, visualization, and business intelligence, which makes it a perfect analytics tool for the business. Furthermore, it is also widely used because of the following characteristics:

  • Flexibility. No matter what€™s the original source of your data, it€™s always extracted and transformed using the same algorithms. 
  • Reliability. A data warehouse is always updated due to the scheduled time, which significantly reduces the impact of the momentary changes. 
  • Scalability. Can be utilized for any data size and easily adjusted for any storage space. 

Data warehouse works with structured and processed types of data and provides the read-only queries for aggregating and summarizing data. The on-write and pre-processing features make it perfect for business analytics implementation.

The use cases for the data warehouse are often related to the banking and finance, public sectors, or hospitality industries – all these imply the data preprocessing before its storage. 

Data Lake Vs. Data Warehouse: What Is The Difference?

Data Lake: Definition, Features, and Sectors of Use

Data lake indicates the system that stores the data in its original format, and usually includes the structured (tables or graphs), semi-structured (CSV, JSON, logs), unstructured (emails, documents), and binary data (audio, photos, etc) for holding. 

The main characteristics that can distinguish it from other data systems are as follows:

  • Easy to use. The data lake can store different types of data from any source for its further analysis and relocation.
  • Organized and structured. Data is collected on a real-time basis and stored in its original format.
  • Affordable. Offers cost-efficient prices for any size of data. 
  • Adapted to any time frame. Can be updated in real-time or when needed. 
  • Unlimited storage space. Provides nice solutions for big data storage. 

Unlike the data warehouses, data lake perfectly works with different types of data and is mostly appreciated for its cost-effective big data storage. The features provided with this system are mainly utilized by the data scientists and engineers who need enough space for storing all the important data and project details, thus employing that system for deep learning, real-time analytics, and others. 

Data Lake Vs. Data Warehouse: What Is The Difference?

Taken from https://www.n-ix.com 

The industries, where the data lake is used, are usually related to healthcare, education, transportation to provide real-time insights and a list of future predictions that can detect and prevent various potential issues, etc. These areas usually need data post-processing procedures that can be easily fulfilled with the data lake system. 

Which One is Better to Use?

To sum up, the issue of using the data lake and data warehouse system solely depends on your needs, goals, and expectations. With the data warehouse system, you can work with the organized and pre-sorted data for your further purposes, while the data lake system allows you to store the data in its original size and formats. 

Thus, after you know the main characteristics of each as well as the industries it is traditionally used for, it€™s much easier to define the system which works best for your business.