Question

1) How do firm strategy, technology, investment, ethics, supply networks, production, markets, geography, and government affect the emergence of the data analytics industry?

Answer 1

     Data is now a key business asset , and it is revolutionising the way companies operate , across most sectors and industries .And if every business is a data business , every business therefore needs a robest data strategy.Instead of startingwith the data itself , every business should start with strategy.At the stage, it doesn't matter what data is out there , what data you are already collecting, what data your counter parts are collecting, what new forms of data becoming available. A good data strategy is not about .what data is readily or potentialty available-it is about what your business wants to achieve, and how data can help you at there.

    It been observed that in large tech based organization , leaders are trying to synergize assertive technology to run more intelligent data analysis.More and more SAS based analytics providers shall combine these tools as data by itself becomes complex as some of the industry sectors goes through a marked revolution by itself.

   While all succesfull enterprises capitalise on data and analytics to some degree, new research from forbes insights and sisco shows how pervasive modern analytics strategies have become with in nearly all bussiness in itiatives.infact , 51 % of C-SUITE executives at large enterprises in both north america and europe say analytics will only continue to grow in importants for maintaining and growing market share over the next two years. To reep the rewards of data - driven business initiatives , enterprises must make targeted investment in traditional and emerging analytics tool as well as in underlying IT infrastructure to support them

Most of the issues with data analytics arise as a result of a lack of information provided to customers.This can be in the form of non disclosure of what is being collected. what the purpose of the collection is, or who is collecting the data .This is the point at which collecting costumer data can stray from what is ethical.

In current competetive environment supply chain proffesionals are struggling in handling the huge data in order to reach integrated , efficient ,effective and agile supply chain .hence , explosive growth in volume and different types of data through out the supply chain has created the need to develop technologies that can intelligently and rapidly analyze large volume of data

Advanced analytics and modelling required the retrieval and cleanshing of data structured appropriatly for the platform being used.Applying advanced analytics to manufacturing operation requirs a combination of data scientists , advanced analytics platform specialist, and manufacturing subject matter experts-as well people who can serve as liaisons between this various constituencies.

The data science platform by component covers platform and services .The platform segment out perform the services segment and is anticipated to required a higher market share during the forcast period due to the growing adoption of the data science platform among small and medium - sized enterprises.