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"Big Data" refers to the vast amount of information businesses are gathering these days. This information comes from a host of sources – social networks, sensor networks, customer chat sessions – and includes both online and offline data. All of the data together becomes so immense that is too difficult to process using traditional methods, such as databases and software. Businesses that can successfully cultivate new ways to analyze the data are finding a hidden treasure of valuable information on the customers and clients that in the end helps make better, more profitable business decisions.
Businesses now are using Big Data to help improve operational practices by identifying problems that may exist, and to help identify new marketing opportunities by analyzing the data to learn more about who their customers are so they can better target them. In addition, many companies are starting to incorporate Big Data analytics into their hiring practices to make sure they are attracting and identifying the top talent.
The Big Data industry is expected to grow by leaps and bounds in the next few years. A recent study revealed that the revenue from Big Data is expected to grow from its current $5 billion mark to more than $50 billion by 2017. A separate study of more than 700 marketers showed that almost 70 percent of companies plan to spend more on data-related marketing initiatives this year, with a heavy emphasis on hiring specialists who can analyze the massive amount of data they are collecting.
Big data analytics
Big data analytics refers to the highly difficult task of turning that mountain of data into easy-to-decipher information that will lead to improved decision making. One of the leaders in Big Data analytics is computer giant IBM, which cites on its website that by using "advanced techniques such as text analytics, machine learning, predictive analytics, data mining, statistics, and natural language processing, businesses can analyze previously untapped data sources independent or together with their existing enterprise data to gain new insights resulting in significantly better and faster decisions."
The three main technologies associated with Big Data analytics are the NoSQL database, which is specially designed to handle large amounts of data; MapReduce, a programming model that can process massive amounts of unstructured data, such as images, videos, emails and documents; and Hadoop, which lets business examine data on a variety of different servers.
Typically, businesses don't employ the skilled IT specialists required to implement and execute big data analytics. The majority of businesses, big and small, hire outside vendors to handle the data analyzing needs.
Big data companies
With big data becoming an increasingly important tool for businesses of all sizes, the market has been flooded with companies able to provide analytical skills. There are larger technology consultants, like IBM and HP, as well as smaller businesses solely dedicated to big data analytics, like Birst and GoodData. There are literally hundreds of different big data firms, and each offers a variety of analytical services.
A recent report from Wikibonrevealed the top big data vendors – based on revenue – from the past year. Topping the list was IBM, bringing in more than $1.35 billion in big data revenue. The computer giant was followed on the list by HP, Teradata, Dell and Oracle. Among the companies that focus all their work on big data, the highest revenue generators were Splunk, Opera Solutions, Mu Sigma, Palantir and Cloudera.
Among the things to consider when hiring a big data analytics firm are cost – some services can run as much as several hundred thousand of dollars while other services come much cheaper; the specific types of analyzing they do – operational marketing, or hiring; and whether those analyses are going to provide the valuable answers a business is looking for.