When companies started to focus on data, with the creation of reports, the growth of CRM, ERP, storage and processing were expensive, companies were selective with what data to collect and store, reports were lean, there was not an abundance After that, of information . It was difficult to analyze, creating a new source of information was costly, it required a project. prioritizing IT over other initiatives with better profitability. At the beginning of the dissemination of data culture, the extraction of reports was mostly done by the IT area. You needed to stop a developer ask to take a report from the database, often from the production environment .
Think of a company that went through
Then within the business areas, people with knowledge in SQL and databases began to appear to carry out these extractions, the concept of Spreading along with BI. Then came data marts, data lakes, and today we have the storage hype. The data mesh, which assigns an owner to After that, the data and helps to mitigate the problem of Rich People B2C Phone Number List cemeteries. Think of a company that went through all this evolution, with text reports generated by the. IT area, years later the creation of a database used by the business areas. Then a data area centralizing information from the entire company. imagine how much data obsolete are stored until today.
This lower cost of storage
have a large storage capacity at a low cost, compared to years ago. Given this scenario, business requests for new sources of information After that, were becoming more and more comprehensive. Aiming at deeper and more detailed analyses. This lower cost of storage and ease of collection ended up reducing the requirement for defining business EK Leads needs. Situations in which the requester of a new source of information. Barely knows the data he is requesting are increasingly frequent. Creating situations such as when in doubt about which columns you will need, bring everything . Aphrase apparently as innocent as this one, and as recurrent on the day of the data teams, ends up being one of the villains.
