7 Reasons Why You Should Consider a Data Lake - A data lake doesn’t need to be the end destination for you need data. Data is constantly flowing, moving, and changing its form and shape.
With the volume, velocity, and variety of today’s data, we have all started to acknowledge that there is no one-size-fits-all database for all data needs. Instead, many companies have shifted towards choosing the right data store for a specific use case or project. The distribution of data across different data stores brought the challenge of consolidating data for analytics. Historically, the only viable solution was to build a data warehouse — extract data from all different sources, clean and bring it together, and finally, load this data to polished Data Warehouse (DWH) tables in a well-defined structure. While there is nothing wrong with this approach, a combination of a data lake and a data warehouse may be just the solution you need. Let’s investigate why.
In Conversation With Dr Suman Sanyal, NIIT University,he shares his insights on how universities can contribute to this highly promising sector and what aspirants can do to build a successful data science career.
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Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments. Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.
The biggest problem we face today is the commoditization of education. Individuals and corporations alike would like quality courses to be offered by the best faculty at the lowest price
For this week’s latest data science job openings, we have come up with a curated list of job openings for data scientists and analysts.