When the first release of Spark became available in 2014, Hadoop had already enjoyed several years of growth since 2009 onwards in the commercial space. Although Hadoop solved a major hurdle in analyzing large terabyte-scale datasets efficiently, using distributed computing methods that were broadly accessible, it still had shortfalls that hindered its wider acceptance.
Limitations of Hadoop
A few of the common…
Added by Packt Publishing on May 3, 2018 at 1:30am — No Comments
Outdated, inaccurate, or duplicated data won’t drive optimal data driven solutions. When data is inaccurate, leads are harder to track and nurture, and insights may be flawed. The data on which you base your big data strategy must be accurate, up-to-date, as complete as possible, and should not contain duplicate entries. Clean data results in…Continue
Added by Favio Vázquez on August 18, 2017 at 8:00am — No Comments
Note: Opinions expressed are solely my own and do not express the views or opinions of my employer.
As a data scientist who has been munging data and building machine learning models in tools like R, Python and other software(s) (open source and proprietary), I had always longed for a world without technical limitations. A world which would allow me to create data structures (data scientists usually call them vectors, matrices or dataframes) of virtually any…Continue
Added by Fawad Alam on May 18, 2015 at 8:30am — No Comments