How important are big data certifications
Data lakes are repositories that store exact or near-exact copies of your data in a single directory. This technology is becoming increasingly widespread in companies that need a large, holistic repository for their data. It is also cheaper than databases.
With data lakes, you get a pristine view of your data so that your top analysts can try their refinement and analysis techniques outside of traditional data stores (such as data warehouses) and completely independent of the frame of reference. If you want these highly skilled people to continually develop their skills and explore new ways of analyzing data, there is no way around data lakes.
Data lakes require ongoing maintenance and a plan for how you will access and use the data. Without this maintenance, you run the risk of your information becoming inaccessible, unwieldy, expensive, and useless, i.e. garbage. Data lakes that are no longer accessible to the user are also called "data swamps".
Large organizations have multiple lines of business, each with its own unique set of requirements. Because of the notorious scarcity of resources, these business areas are in constant competition for access to data and infrastructure in order to be able to carry out their analyzes. You cannot solve this problem with data lakes. This only works with multi-tenant workload isolation and data sharing. What does that mean exactly?
Instead of completely duplicating your data every time a business unit accesses it (including administration such as writing scripts to copy data so that everything works), you can use this solution to reduce the number of copies to a few. These can then be used jointly by all business areas through containerization or virtualization of the data analysis tools.
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