The biggest big data challenges
We all know that Necessity is the mother of invention and we don’t want to stop at any point in our life because it’s in our gene.
The complex business environment in the world made to invent the concept of big data. Nowadays, data and how to use them make the company different from each other and most important to stay in business. For that companies transform as much as data into a meaningful product with data-driven discoveries for the users. Right analytics on data maximise revenue, improve operations and mitigate risks. According to Demirkan and Dal, big data has following six “V” characteristics i.e Volume, Velocity, Variety, Veracity, Variability and Value. The biggest big data challenges are a bit opaque to see.
IDC predict big data revenue sales will increase more than 50% from nearly $122 billion in 2015 to more than $187 billion in 2019. Nearly 73% of companies increase investing on analytics to transform data into gold but 60 percent of them feel that they don’t have the proper tool to get insight from data. Research predicts that half of all big data projects will fail to deliver desired output.
When Gartner asked what the biggest big data challenges were, the responses suggest that while all the companies plan to move ahead with big data projects, they still don’t have a good idea about what they’re doing and why. The second major concern is not establishing data governance and management. Thomas Schutz, SVP, General Manager of Experian Data Quality. says that “The biggest problem organisations face around data management today actually comes from within,” and “Businesses get in their own way by refusing to create a culture around data and not prioritising the proper funding and staffing for data management.”
There are many challenges but data related issues are biggest challenges in big data.