Big Data is here to stay and there are definitely no two ways on the same.
At the same time the unique opportunity which Big Data brings to the current technology landscape also brings along-with few unique challenges which needs to be understood and tackled with:-
1) Effective Analytics
Merging the traditional structured data assets and the unstructured/alternative structured data assets towards holistic analytics would remain one of the key challenges for Big Data as a Platform.
2) Privacy and Security
The growing volume/variety/velocity of data assets would undermine the traditional Privacy and security modes. Hence it is imperative to develop evolved processes and framework to support the changing needs of Big Data.
3) Performance with Schema on Read
The shift from the age old Schema-on-write paradigm which most of the current Data-warehouses follow. To the schema-on-read paradigm which is propagated by the likes of Data Lakes in the Big Data world, will bring on a critical challenge to meet the same performance benchmarks which the Data Retrieval applications used to get from the old warehouses.
4) Co-exist or Replace Data-warehouses?
The key question which many of the Big Data practitioners are today raising is how should the Big Data platforms evolve in an enterprise. Should they co-exists and be limited to play the role of all encompassing Landing layer for the warehouse. Or should it move ahead and replace the warehouses by directly bridging the gap between the data generating source systems and data consumption systems.
5) Survival of a Distributed Model in a relational world
Big Data has become synonymous with the Hadoop Data Platform as its strongest implementation framework. However the fully distributed mode of functioning with Hadoop will bring in intrinsic challenges when business apps and logic accustomed to the relational model of functioning start getting assimilated into the underlying distributed framework of Hadoop powered be MapReduce as the data processing mode.
At the same time the unique opportunity which Big Data brings to the current technology landscape also brings along-with few unique challenges which needs to be understood and tackled with:-
1) Effective Analytics
Merging the traditional structured data assets and the unstructured/alternative structured data assets towards holistic analytics would remain one of the key challenges for Big Data as a Platform.
2) Privacy and Security
The growing volume/variety/velocity of data assets would undermine the traditional Privacy and security modes. Hence it is imperative to develop evolved processes and framework to support the changing needs of Big Data.
3) Performance with Schema on Read
The shift from the age old Schema-on-write paradigm which most of the current Data-warehouses follow. To the schema-on-read paradigm which is propagated by the likes of Data Lakes in the Big Data world, will bring on a critical challenge to meet the same performance benchmarks which the Data Retrieval applications used to get from the old warehouses.
4) Co-exist or Replace Data-warehouses?
The key question which many of the Big Data practitioners are today raising is how should the Big Data platforms evolve in an enterprise. Should they co-exists and be limited to play the role of all encompassing Landing layer for the warehouse. Or should it move ahead and replace the warehouses by directly bridging the gap between the data generating source systems and data consumption systems.
5) Survival of a Distributed Model in a relational world
Big Data has become synonymous with the Hadoop Data Platform as its strongest implementation framework. However the fully distributed mode of functioning with Hadoop will bring in intrinsic challenges when business apps and logic accustomed to the relational model of functioning start getting assimilated into the underlying distributed framework of Hadoop powered be MapReduce as the data processing mode.
6 comments:
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Nowadays data is everywhere no matter whether you are doing a school project or you are heading a corporate organization. Big data is in a constant mode of evolution. It has created huge leaps of growth for businesses who have been using it. The massive increase in the volume, variety, and velocity of data showcases that big data will definitely encounter. Last year my brother have joined a good institute to complete Big Data Analytics training.
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