Big Data

what is big data.?

Big data is a term that describes the large volume of data – both structured and unstructured – that deals a business on a day-to-day basis. But it’s not the amount of data that’s important. It’s what organizations do with the data that matters. Big data can be analyzed for insights(accuracy) that lead to better decisions and strategic business moves.


Why Is Big Data Important?

The importance of big data doesn’t revolve around how much data you have, but what you do with it. You can take data from any source and analyze it to find answers that enable 

1) cost reductions,

 2) time reductions,

 3) new product development and optimized offerings, 

 4) smart decision making. When you combine big data with high-powered analytics, you can accomplish business-related tasks such as:

• Determining root causes of failures, issues and defects in near-real time.
• Generating coupons at the point of sale based on the customer’s buying habits.
• Recalculating entire risk portfolios in minutes.
• Detecting fraudulent behavior before it affects your organization.

Volume. Organizations collect data from a variety of sources, including business transactions, social media and information from sensor or machine-to-machine data. In the past, storing it would’ve been a problem – but new technologies (such as Hadoop) have eased the burden.

Velocity. Data streams in at an unprecedented speed and must be dealt with in a timely manner. RFID tags, sensors and smart metering are driving the need to deal with torrents of data in near-real time.

Variety. Data comes in all types of formats – from structured, numeric data in traditional databases to unstructured text documents, email, video, audio, stock ticker data and financial transactions.

Variability. In addition to the increasing velocities and varieties of data, data flows can be highly inconsistent with periodic peaks. Is something trending in social media? Daily, seasonal and event-triggered peak data loads can be challenging to manage. Even more so with unstructured data.

2.What are the drivers for big data?
Governance - Good governance encompasses consistent guidance, procedures and clear management decision-making. Organizations need to ensure standard and exhaustive data capture; they need not protect all the data, but they need to start sharing data with in-built protections with the right levels and functions of the organization.

Management – Integrating and moving data across the organization is traditionally constrained by data storage platforms such as relational databases or batch files with limited ability to process very large volumes of data, data with complex structure or without structure at all, or data generated or received at very high speeds.

Architecture – Data architecture should be prepared to break down internal silos, enabling the sharing of key data sets across the organization and to ensure that learnings are being captured and relayed across to the right set of people in the organization in a timely and accurate manner.

Usage – The results of big data can beneficial to a wide range of stakeholders across the organization — executive management and boards, business operations and risk professionals, including legal, internal audit, finance and compliance; as well as customer-facing departments like sales and marketing. The challenge is having the ability to interpret the huge amount of data that can be collated from various sources.

Quality – The quality of data sets and the inference drawn from such data sets are increasingly becoming more critical. Organizations need to build quality and monitoring functions and parameters for big data. Correcting a data error can be much more costly than getting the data right the first time — and getting the data wrong can be catastrophic and much more costly to the organization if not corrected.

Security – Companies need to start establishing security policies which are self-configurable: these policies must leverage existing trust relationships, and promote data and resource sharing within the organizations, while ensuring that data analytics are optimized and not limited because of such policies.

Privacy – The increased use of big data challenges the traditional frameworks for protecting the privacy of personal information, forcing companies to audit the implementation of their privacy policies to ensure that privacy is being properly maintained.

Big data analytics is the process of collecting, organizing and analyzing large sets of data (called big data) to discover patterns and other useful information. Big data analytics can help organizations to better understand the information contained within the data and will also help identify the data that is most important to the business and future business decisions. Analysts working with big data basically want the knowledge that comes from analyzing the data.
                                                                                                                                source:internet