Sep 16, 2024
What is Data Lake?
A data lake is a centralized storage solution for many big firms. It can store data in its raw native form without any compression. It does not matter if the data that is being stored is structured or unstructured. The method of storing data in data lakes is a bit different compared to the traditional storage solution-data warehouses. Rather than storing data in tables and hierarchical dimensions, data lakes stores data in files or object storage.
Why do Organizations Use Data Lakes?
Organizations that use data lakes are destined to perform better than their competition in all its simplicity. According to a survey, those companies who use data lakes and take advantage of its perks tend to outperform their peers by a margin of 9%. On a small scale, that does not seem like much, but 9% can hold a value of millions of dollars on a grander scale.
A data lake allows companies to absorb data in any form necessary and at any speed. It provides companies with a secure and scalable platform. You can store data from anywhere without compromising on anything; the data can be from the cloud, on-premises, or edge computing systems. Data lakes do not compress the stored data, which means they can be stored in their original form. They are the perfect platform for companies that prefer to use data for big data analytics and other data science applications. These applications require a tremendous amount of data that also involves advanced data analytics such as machine learning and data mining.
Firms using data lakes are able to do different kinds of analytics involving machine learning over various sources like social media, log files, data from click streams, and the internet-connected devices stored in the data lakes. Operations like these help them to identify and create opportunities for business growth by attracting new customers and retaining new ones, maintaining devices, and, based on the data making informed decisions.
Without data lakes, a company lacks a centralized data storage solution that data scientists and analysts can use and take advantage of to find and analyze relevant data. The process becomes much harder without it, and organizations cannot take full advantage of their data to make informed decisions and useful future strategies.
Some Important use cases of Data Lakes
Movement of Data
These systems give you the freedom to import data in real-time without any bar set on the amount of imported data; you can import any amount of data without any hurdles. Data lakes allow you to store data in its real and native format without any change. This functionality means you can scale up to any data size without wasting time on structuring and data transformation.
Machine Learning
Using data lakes, organizations can forge various types of insights and perform machine learning to build models to forecast the most probable outcomes. A company uses predictive models to analyze their customers’ buying behaviors which can direct them to improve their online advertisement strategy and personalize their marketing schemes if necessary. Opting for this method allows companies to predict the likely outcomes, due to which they can choose the best suitable method to obtain optimal results.
Analytics
You have the freedom to use the tools within your comfort zone because of the versatility of data lake analytics. Different personnel from your company, such as data scientists, business analysts, and data developers, can use tools and frameworks of their preference in order to access the data that lies within. Data lakes allow you to analyze your data without needing to move that data into another analytics system.
With the help of analytics, companies can take advantage of recent trends and change their business strategies to serve the market demand. Data lakes can help you manage business operations more efficiently, make better decisions, and take advantage of new opportunities.
Some other advantages of data lakes:
- They are cost-efficient and relatively cheaper to implement as the technologies used to build them, such as Hadoop and sparks, are open source and are easily installable on cost-saving hardware.
- Businesses can use a wide variety of analytics methods to analyze the data in data lake environments, including machine learning, predictive modeling, etc.
- It can also help in cost cutting in the IT and data management department as it can eliminate duplicate data platforms.
Conclusion
Data lakes are a useful asset that can turn the tide of businesses if used in a correct manner. It can help your business in making informed decisions that will help increase revenue and build a new customer base. You can take advantage of the ongoing trend and adapt to grab the opportunity that the trend presents. You can analyze the behavior and attitude of your current customer towards your products and improve them to retain those customers and attract new ones. If you’re ready to take your business to the next level, data lakes can be the best method to do so.
Then Why Axeno? Because, Here at Axeno, our goal is to provide professional services that we designed to facilitate the use of ever-evolving technology by enterprises and end users. We focus on improving user experiences and Digital Transformation services. Our services are designed to nurture your specific business needs and user requirements.
