Data analytics is big time changing the way organizations think, execute and perform. It has become a part of everyone's daily lives - but most of us are yet to realize it. The term data analytics or data science makes you imagine of computer-laden corporate offices, where suited booted data scientists or data analysts work to deliver data analytics solutions that answer real business challenges.
It is said that knowledge is power; and especially in recent years, it is encountered increasingly in form of digital data sets - structured as well as unstructured. The more data and information that you possess, the more perfect are your plans, better are your decisions, planned are your tactics and strategies, and success is unlimited.
It has been an unsolved mystery for companies if they should get their data cleansed first to opt for data analytics or if they should opt for data analytics to conclude whether their data is dirty. It comes back to the question, Which came first: the chicken or the egg?
Data & Analytics have become main-stream. Executives and their boards are increasingly starting to question whether their organizations are truly realizing the full value of the insights. A study suggests that 58% of organizations have difficulties evaluating the quality of the data and its reliability, raising a big question to the stakeholders as to " can you trust your data?"
Furthermore, retailers are actively utilizing structured and unstructured data about customer behavior and clustering techniques to help improve performance. * Deciding on shop location One of the most strategic decisions, with everlasting effect, in the retail industry is choosing a store location.
If a company or enterprise is considering to get business intelligent, it becomes mandatory for them to give due consideration to the concept of smart
Businesses across the globe are facing the brunt, one of huge data influx and second of increasing data complexity and of course the market volatility. To address these challenges, companies and all their verticals are turning to data-driven analytics and insights as a means to better understand their organization's customer bases and to grow their businesses; and manage the increasing uncertainty up to a certain extent.
For statistical models, selecting those predictors is what tests the steel of data scientists. It is really challenging to lay out the steps, as for every step, they should evaluate the situation and make decisions for the next or upcoming steps.
Increased exposure to data and analytics has brought questions about the trust that is placed in it. Here are 4 reasons we should discuss trust data analytics
There is a pragmatic shift in the way most business operations are conducted across multiple industrial domains. This changing equations, have eventually resulted into fierce competition - Even the most non-competitive domains like insurance sector is now getting the taste of cut-throat competition.