The Big Data and Analytics innovative technology helps businesses to keep and analyse large sets of data to get insights and business value. The growth of this data is presenting opportunities as well as challenges for organisations. Despite the challenges in USA Big Data market, businesses continue to embrace innovations in big data technology. Semi-structured and unstructured data being produced in huge quantities are rich sources of information that tell businesses exactly what consumers need and want and why and how they buy. Some of the major issues and challenges in the USA Big Data market are as follows:
Data is growing at an alarming rate in many USA organizations and keeping it is becoming a big challenge. For instance, the National Aeronautics and Space Administration (NASA), an independent agency of the USA government responsible for the civilian space program, aeronautics and aerospace research, collects many petabytes of data per year from numerous current active missions. The agency does this every hour, every year and the rate of collection is growing exponentially. Storing such data is a massive challenge for the US government.
While using Big Data technology, keeping the data secure is a major challenge for many companies in the US. Any organization that intends to collect, store, and use Big Data, must invest in adequate security. Large sets of data are a tempting target for cyber attackers. When attackers set their sights on data repositories, the consequence can be devastating for the affected companies. Terabytes of data in those repositories may include trade secrets, employee data, and customer data. Major 2016 breaches in the US occurred in the University of Central Florida, U.S. Department of Justice, Internal Revenue Service, and UC Berkeley.
Organizations in the US are feeling the shortage of data talent. Not only is there data scientists shortage but to successfully implement any big data project needs a sophisticated team of data scientists, developers, and analysts who have sufficient knowledge to identify valuable insights. According to a 2015 MIT Sloan Management Review, 40% of the businesses surveyed were struggling to get and retain the data analytics talent. In addition, Deloitte’s Analytics Trends 2016 report noted that although the number of university data science and analytics programs is rising in the US, companies nonetheless can’t find enough sufficiently trained individuals to meet demand.
The quality of data is not a new issue, but the ability to keep every piece of data that an organization produces in its original state compound the problem. All too often, businesses collect data that is filled with mistakes, incomplete values, and errors. This is known as dirty data, and it can be an obstacle to organizations hoping to use that data to improve. According to The Data Warehouse Institute (TDWI), dirty data costs U.S. companies around $600 billion every year.
It’s hard to estimate the cost of a big data projects, and considering how quickly they scale, they can quickly eat up resources. The challenge lies in calculating all costs of the project from hardware acquisition, to paying a cloud provider, to contracting additional personnel. Companies pursuing on-premises projects must take into account the cost of training, expansion, and maintenance. Many US businesses agree that it is costly to operate and manage Big Data technology. That is evidenced by the fact that the average pay for a data scientist in the US is $91,588 per year
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