Did you say data lakes?
03 January, 2022
This morning you almost dropped your cup of coffee, learning that your data scientist was not talking about her holidays but massi...
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Why should you care about all that data? Why shouldn’t you let it rot deep in your shelf? Well, because you made 90% of the effort collecting and storing it. Why stop on such a right track?
If you are not familiar with data lakes, we advise you to read: Did you say data lakes? first.
Data lakes and data warehouses are two complementary tools. While a data lake stores your data, a data warehouse helps you access and manage it so that you can use it for business matters. Thus, it logically takes action after your data has been collected.
In this article, we intend to give you the keys to understanding what data warehouses are and how it can help you get a clear insight of your business.
Flows of data arrive on a data warehouse to be queried. As a true warehouse, a data warehouse stores data, formats it, processes it so that it can be understood by data scientists and then exploited by the board on their decision making process.
In other words, a data warehouse allows the passing from figures to analytics, from unstructured and indigestible data to understandable data.
Nowadays, data has become essential for business understanding. If small companies can make do with spreadsheets, Big Data has made it impossible with businesses with large ambition to process data manually. A data warehouse becomes indispensable as soon as you want to process big amounts of data from multiple sources: users’ information, business’s data...
Briefly, you can collect data, download, store, access, analyze and sort it before making decisions based on the reporting.
Your work team is not made up of data scientists, and that is perfectly fine. Do you have to give up on analytics? Absolutely not. To have access to your data is a thing, but to understand it will bring you so much more than that.
Thanks to data warehousing, they will soon be able to surf the wave of data analytics and adapt their strategies to data they smartly selected. To be completely transparent, we won’t bother you much with OLAP, ETL and other acronyms. We’ll keep it simple.
A data warehouse stores data in a structured way which makes it easier to analyze it a second time. In such a warehouse, the storage of data is called “integrated storage” for data coming from different sources is stored altogether.
The data is said to be non-volatile on a data warehouse as it can’t be edited once stored.
So, how does it work?
Well, in a nutshell, formatted data arrives on a pipeline (an ETL: extract, transform and load) to a data warehouse. It is then stored in the warehouse and processed in that same place to support your organization’s decision making.
What does it include? What do you have access to?
It depends on the data warehouse, but usually: a database to store your data, an ETL solution, reporting tools and a visualization board to help you present your data in a business friendly language.
Here is a clear diagram that should help you understand the interest of a data warehouse.
Can data lakes replace data warehouses? Is it one of these useless tools that stay in the toolbox forever? Not at all. Data lakes do not allow rigorous storage of data and thus, do not permit your IT to question data as easily as they would in a data warehouse.
Data lakes may be easier to use but the results are much longer to be provided by such a system due to the complex and unstructured format of data.
The use of a data warehouse can truly benefit your organization, even if it has some undeniable drawbacks. Among tools, this one is probably one of the most interesting.
This analytics tool helps you:
Before taking the decision to use a data warehouse, you should be aware of its main drawbacks:
Just a quick reminder on why a data warehouse could help your business:
If you need any advice on how to implement a data warehouse or support to keep track of it, contact our dedicated IT team.
By Emma Jeanpierre
23 Sep, 2021