A collection of data from traditional sources such as structured data from many data bases, files, and documents and social media sources such as unstructured data from Twitter, Facebook, Web pages, Blogs and forums inside and outside an organization that a company can analyze to make better decisions and gain competitive advantage.
Big data is being generated by everything around us at all times. Every digital process and social media exchange produces it. Systems, sensors and mobile devices transmit it. Big data is arriving from multiple sources at an alarming velocity, volume and variety. To extract meaningful value from big data, you need optimal processing power, analytics capabilities and skills.
Big data is changing the way people within organizations work together. It is creating a culture in which business and IT leaders must join forces to realize value from all data. Insights from big data can enable all employees to make better decisions—deepening customer engagement, optimizing operations, preventing threats and fraud, and capitalizing on new sources of revenue. But escalating demand for insights requires a fundamentally new approach to architecture, tools and practices.
Big data is a segment of IT such as security, Mobile, Database, programming etc. Big data is not a single tool but represents a collection of tools. Big data has gone mainstream, say the experts, as a society we have been adding 200 TB data a day from traditional transaction data and also from unstructured data from millions of websites. For example Amazon is selling products from its database ( Structured ) but would like to know what people are talking about it in social media. There is a need to combine Amazon product and customer data base with unstructured data from the web. Hadoop is one of the tools used to analyze unstructured data
The process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations and other useful information.
Business analytics comes in four main flavors:
Descriptive analysis: Analyzes past events for insight
Predictive analysis: Provides a probability of what might happen in the future.
Prescriptive analysis: Foresees what will happen and when it will happen, but also why it will happen an provides recommendations how to act upon it in order to take advantage of the predictions.
Cognitive analysis: use natural language processing and machine learning to make complex decisions using extraordinary volumes of fast-moving big data.
Economic benefits of Hadoop will make adoption essential, not optional, for enterprises as they move into 2015. Hadoop is and open-source technology used to organize and analyze vast amounts of structured and unstructured data, such as posts to social media sites, digital pictures and videos, online transaction records, and cell phone location data.
And putting dollars aside, big data analytics are quickly becoming part of everyone’s job, says Tom Davenport, a Distinguished Professor of Information Technology and Management at Babson College and author of Big Data at Work. He asserts that we are entering the Analytics 3.0 era, in which insights can be delivered anytime you need them via any device.
Big Data is not merely the accumulation of vast amounts of information, but a collection of interconnected and interrelated data points that, when analyzed carefully, helps business leaders make decisions that lead to increased profitability and job creation, assists doctors and scientists in understanding critical factors about health care, helps policymakers better protect the public from potential terror attacks, and much more. To be clear, advanced analytics techniques go beyond merely describing the data that is available. If you want to make better decisions you decide what important data you need to know, collect it in ways that operations researchers can analyze, and think: What assumptions must I make before I proceed?
Big Data use case studies:
Your health insurance provider can use analytics to help give you better diagnosis and treatment options, and try to predict health issues before they happen, by quickly capturing and making sense of complex patient and medical data.
Data is emerging as the world’s newest resource for competitive advantage.
Decision making is moving from the elite few to the empowered many.
Value of data
As the value of data continues to grow, current systems won’t keep pace.
New skills are needed to fully harness the power of big data. Though courses are being offered to prepare a new generation of big data experts, it will take some time to get them into the workforce. Meanwhile, leading organizations are developing new roles, focusing on key challenges and creating new business models to gain the most from big data.
The demand for data and analytics resources will reach 4.4 million jobs globally, but only one-third of those jobs will be filled. The emerging role of data scientist is meant to fill that skills gap.
While big data can provide significant value, it also presents significant risk. Organizations must be proactive about privacy, security and governance to ensure all data and insights are protected and secure.
From data-driven marketing and ad targeting to the connected car, big data is fueling product innovation and new revenue opportunities for many organizations.