The transformative impact of the data market

[najmulislam77]

The data mart is emerging as a new concept that includes everything learned about data lakes and goes even further. Today’s businesses need to incorporate new capabilities to efficiently manage, analyze, and use an exponential volume of data.

Lots of data but no value
Every modern enterprise must manage a vast volume of data that is continually growing like never before. Big data has increased the velocity and variety of data, creating significant opportunities and challenges. In addition, applications installed in the cloud, server-side log data, IoT devices, and SaaS providers are also growing.

In this complex context, machine learning technologies only produce knowledge when they receive the right type of data, and companies can take advantage of information if they have architectures, tools and systems capable of tracking, transforming, sharing and delivering it in the right time and place.

This is not happening in many companies yet: information jamaica phone number lead remains stagnant and does not arrive in a timely manner to make efficient and beneficial decisions. We must not forget that more data does not mean more benefits; in fact, having unused data produces more cost than value .

Although there are technologies such as data lakes and data warehouses that offer multiple advantages in this regard, by themselves they cannot provide a complete answer to the problem of large volumes of data and its challenges for organizations.

The emergence of data warehouses created a business model that became the basis for reporting, BI and data discovery. This technology gives governance a key role, but it does not have the capacity to provide rapid information or efficient Big Data panoramas.

As for data lakes, they were created with the aim of generating commercial value from Big Data, storing huge amounts of data to analyse them and thus achieve competitive advantages.

But there's a problem: Companies have typically deployed data lakes and data warehouses without a clear business context for the data , rendering the information unusable and even dangerous.

The advantages of using data lakes correctly are:

Large data storage
Storing Diverse Data
Efficient pre-analysis visualization
Data ready for yet unknown business questions
Compatibility with numerous consumption profiles
Single repository for column-based, structured and document-based data.
However, data lakes have not found their rightful place in data analysis and value. Although this tool provides a great capacity for storing and analyzing a company's information, it is true that in order to find value, other resources must be used to achieve it .

From data lakes to the concept of data market
To efficiently manage and govern the messy flows of Big Data, companies must learn to diagram and manage flows for all their data , incorporating new data regularly.

That is, when new data sources arrive, they must be evaluated and incorporated into the compendium that is already operating in the company . This does not simply consist of placing them in one place, but rather in an incorporation process that is automated and resizable .

When this has happened, all users must immediately access the information in order to improve it, using commercial metadata. Remember that automated analysis processes, as well as the creation of profiles, enrich the data.

As time goes by, more data will arrive, but there will be more people managing it . This is an important point, since many people must participate in the management and evaluation of the information for the result to be truly valuable. It is a cycle that is sustained, benefiting business activity: As data sets progressively increase, companies develop a broad and solid understanding of them.