*by André Muraki
Data monetization is already part of our day-to-day lives and we receive an avalanche of information on a daily basis that is used to maintain and enhance the business. The way we search for and receive this content can be structured (databases, excel tables, forms, etc.) or unstructured (texts, files, videos, audios, social networks, etc.) – and this is where the challenge for organizations resides .
The advantage of using information has long ago been how we collect, organize, interpret and analyze it to generate insights and turn them into business gains. However, most of it is in a raw state, which is usually stored in a data lake, that is, a repository.
But after all, what is the importance of having and maintaining a data lake? Simple, easy and fast access to unstructured data. The repository centralizes and stores all types of data generated by and for the company. From it, businesses from all segments obtain information that will later be treated and structured to guide strategies and decision-making. But it's worth bearing in mind that in a data lake, what counts is the quantity and not the quality of the data.
When it comes to information ownership and its importance to the company, there is a concept and solution that help us centralize and organize, the data warehouse (DW). Basically, it is a central repository, where all data relevant to the company is stored, which can be organized into strategic groups, such as financial and sales data, for example, and where the information is summarized to be consumed at the end, or that is, by the business areas.
Thus, the difference between data lake and data warehouse is in the way information is arranged in each of these repositories. In the data lake, the data is stored in a raw state, without any treatment. In DW, they are filtered, cataloged or ranked in some way. However, this differentiation of environments can be suppressed and become consolidated.
Future Data Warehouse
As traditional data warehouses have gained in efficiency, analytics infrastructures have become extensive, supporting a range of applications from advanced operational analytics to performance management. And for all of this to work in a way that supported and scaled with high demand, it had to move the data warehouse to the cloud. In the virtual environment, the DW became modern data warehouse (MDW), or modern data warehouse.
MDW allows you to easily gather all data at any scale, structured, unstructured or semi-structured, offering availability and high performance in accessing the information stored at the end of the BI process. In a traditional data warehouse, for example, structured data is compiled in one place, yet it has to be constantly updated because of the sheer volume. What's more: this entire process generates high costs and impacts performance. On the other hand, considering the cloud resources, the MDW does not need local machines for data processing and can be scaled quickly according to the business demand.
The modern data warehouse brings agility, scalability, ease, more performance and a significant reduction in operating costs. But, the main advantage is the speed with which it is possible to generate strategic insights, which guarantee high competitiveness in this new world where the future invades the present at all times. You have to be ahead now.
By André Muraki, Logicalis Data Intelligence BU Manager
Notice: The opinion presented in this article is the responsibility of its author and not of ABES - Brazilian Association of Software Companies
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