Data lake: 4 passos para uma estratégia de sucesso

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Having a data lake (DL) in times of big data is essential for your company to follow a successful strategy and be completely data-driven. Especially due to the storage versatility that this type of repository offers.

However, anyone who thinks that simply having a DL solves all problems is mistaken. It is necessary to adopt effective methodologies to avoid wasting time and money.

Below, check out the 4 steps that Indicium guides your company to successfully use its data lake.

Keep reading.

What is a data lake and why is it important?

Data lake is an indispensable repository when big data is one of the main resources for business analysis and decisions .

It brings many advantages to a company due to the way data is structured and used.

You will understand better below, with the four steps that Indicium guides.

Step 1: migrate to ELT

Having a data lake (DL) in times of big data is essential for your company to follow a successful strategy and be completely data-driven.

One of the biggest attractions of DL is its ability to store all types of data in one place , which does not translate into disorganization.

Quite the opposite!

Structuring data within a data lake helps those who collect this information for analysis because it will already be structured and organized with the appropriate metadata.

And for this process to occur in the best way, Indicium recommends that you adopt ELT instead of traditional ETL.

So, your data team does the extraction, loads the information into the DL and transforms everything within the repository.

Having structured data in a data lake can save a lot of time and money for your company, as it facilitates crucial processes in data projects in general.

Step 2: choose the best technology stack

A company's technological infrastructure strongly influences the results of its data projects. And as you may already know, in the world of technology, only those who keep up to date lead.

That's why implementing approaches like the Modern Data Stack (MDS) is one of the best options for those who want to make the most of the functions of a data lake.

For example, for your data platform to be modern, flexible and scalable, it is necessary for the data to be centralized in a single location in the cloud, in this case, in a DL.

Therefore, the modern approach to analytics is a good way to leverage your data lake, but there are still other good ways to make good use of it.

Step 3: Stay safe

Saying that data is the new oil means saying that it has value. And everything that has value needs to be protected.

With the entry into force of the General Personal Data Protection Law (LGPD), this issue has become even more critical.

Within a modern approach to analytics , for example, information security reaches maturity to allow easy and quick access to analysts without breaking the confidentiality of personal data.

You don't want to lose something so valuable , do you? So, it's better to take good care of it.

A good security strategy is to maintain constant communication between management teams and business teams to guarantee controlled access levels to each dataset.

Step 4: filter the use of indexes

In data lake , proper use of indexes is important for database performance . Because, despite being fundamental in the search for information, indexes take up space.

Sometimes they can take up to 25% of the size of a table.

As DL queries do not require high performance, it is not necessary to use indexes that go beyond primary keys.

This would create unnecessary volumes , affecting data lake efficiency.

Therefore, think together with your team to list only the essential indexes.

You don't have to do everything on your own

Creating a big data strategy to make the best use of your data lake is not an easy task, nor is it something that comes ready-made. It needs to be built.

But you don't have to do everything on your own

Contact Indicium and talk about your project with top professionals. We will structure the best strategy for your company to take off. 🚀

Plataforma de dados
Data lake
Data products

Bianca Santos


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