In that sense, it might seem like we're talking about a unified database, but we aren't. What then differentiates a data lake from a database? Three characteristics:
The Data Lake does not contain the data, but rather connects different databases .
The data that the Data Lake connects can be of any type : from raw, unprocessed data to data organized in a structured database.
As an extension of the previous point, data can also be in any format : from binary code to images and video.
Thanks to Data Lakes, you can combine and augment all the data from different databases with third-party sources to use them as a single data source.
Why is it so important for companies?
Data lakes represent a revolution for businesses similar to that of databases in terms of scale. While the former allowed for centralized information collection and analysis, data lakes combine the possibilities of working with multiple databases without any of their disadvantages .
Thanks to a Data Lake, companies can work with different sources of information in a way that autocompletes, without having to worry about:
Unify its structure
Unify your format
Access all of them separately
All of this is done by the Data Lake itself, and as a result, the potential uses explode. Companies can complete the information in their own databases without the need for new recruitment campaigns telegram number list or overwhelming their contacts with endless forms, and best of all, they can do it in real time.
Benefits of a Data Lake
A Data Lake is capable of connecting your company's different technological platforms with external sources, allowing you, for example:
Analyze and evaluate each of the leads you register in a matter of seconds and automatically.
Study credit risk to determine in a matter seconds whether or not financial services should be granted, and their range.
A study of business potential to define, in real time, the offer with the greatest purchasing potential.
Predict geographic areas of commercial interest , with a view to opening new points of sale and closing those that are less profitable or likely to be cannibalized.
Normalize and correct your own databases to establish better analysis and understanding of your customers and the market.
Reduce the costs of collecting and storing information (between one-tenth and one-hundredth of its current cost).
And your company?
Are you limited in your business opportunities by insufficient data or spending too much time analyzing unstructured databases? At DataCentric, we can help you make sense of your company's existing information and connect with new sources of information that complement and correct potential errors in your customer data.