“There was a Time When it was Impossible to Store Data Without Analyzing. But now, with the advent of Cloud Computing, You Can Load Data Without Analyzing It First. That’s How Data Lake Works and Built on the Philosophy- Load First, Think Later,” unlike Data Warehouse- Think First, Load Later.” 

More than 90% of all business data are in unstructured formats. 

Businesses today need unstructured data as they don’t want only to analyze their operational data. 

At one time, it was impossible to store and analyze such data. 

But now it is with the advent of Cloud Computing that allows loading unstructured data with predefined business requirements easily. 

What Really is Data Lake? Why Does it Even Matter?

Data Warehouse– THINK FIRST, LOAD LATER

At first, there were Databases, then came Data Warehouse, and now we have Data Lake. Data Lake is an emerging technology that has redefined Data extraction, storage, and analysis.

Let us first understand what is Data Warehousing. Data Warehouse is a centralized location where all the data of an enterprise company is stored. But before you store the data, you need to define the business need.

But why do we want to store data in a Data Warehouse?

Suppose we take Walmart, which is the largest retail outlet in the US. 

They have these business requirements-

Which products were sold the most in the last 6 months?

Who were the customers that bought these products?

Where are these customers located?

Different kinds of data, like a customer, product, and sales, are stored in different source systems. 

Similarly, when you visit a retail store or a shopping mall and reach the Point of Sales (POS). POS is a place where you make the purchase, and it’s the time and place where a retail transaction is completed. 

At this point, your data enters into the systems and gets stored in various transactional systems. If you want to merge and analyze this data from a central location, you first extract this data. 

So, the data you need for analysis can reside in any of these systems. It can be in Sales, HR, or inventory source systems. 

Once the data is loaded into Data Warehouse, business analytics and reporting happen on top of this data, later passed on to ETL (Extraction, Transform, Load).

From ETL, you collect the data based on your requirements and finally get stored in the Data Warehouse. Once data is loaded into Data Warehouse, then business analysis and reporting happen on top of this data. Hence Data Warehouse works on the philosophy of THINK FIRST, LOAD LATER. 

This means you first need to know what data you need, and based on your requirements; you fetch the data. 

Data Lake- LOAD FIRST, THINK LATER

Today, when you talk about Business Intelligence or Analysis, you’re mainly talking about a Data Warehouse (mostly supports structured data). Now with a fast-growing technological advancement, data volumes are increasing exponentially. 

Today every small system, sensor, or machine generates insightful data. But this is not structured data. This data includes unstructured data, sensor data logs, online repositories, web servers, databases, APIs, and a lot more. 

Businesses today require unstructured data as they don’t want to analyze only its operational data. At one time, it was impossible to store without analyzing such data. But now, with the help of Data Lake, loading unstructured data has become a lot easier. 

Built on the philosophy of- LOAD FIRST, THINK LATER, you can now load whatever data you have and later analyze how you can use this data. Data Lake accepts all kinds of data structured & unstructured logs, images, everything. It stores everything in its raw state. 

Data Lake acts as a central reservoir that stores without any pre-analysis of data. Once data is in Data Lake, you can use it for multiple purposes. 

 How Data Lake Solutions can Impact Your Business?

• Data Lake allows all employees to access data, not just managers or upper management. An employee has the option of using only those that are essential for his department. An enterprise has the ability to keep large amounts of data for a considerable price.
• Companies can easily hoard their data since Data Lakes offers a huge variation in the types of data. 
• Organizations can store their data in a native format and easily pull required data to any future system. 
• Various departments in any enterprise can access quality data for real-time analytics.
• Data Lake not just supports SQL but also multiple languages.
• It can preserve raw data for data exploration and data science.
• Data Lake handles data at a very high speed giving faster results.
• Data Lake offers scalability at a very affordable price and can store huge amounts of data like multiple media, social data, chat, binary, and other data forms.

Verdict- Which is Better and What to Choose?

Both should co-exist as all your requirements cannot be fulfilled solely by Data Lake or Data Warehouse. So ideally, you should first build a Data Lake and then derive various Data Warehouses from it. Data Lake is a good platform for advanced data analytics. With technologies like Machine Learning and AI, you can process any data, which is why Data Scientists come into the picture now. Data Lake and Data Warehouse are different but work together fulfilling your business requirement. To know more, connect with us to scale up your business.