Big Data - Definition, Importance, Examples & Tools

BIG DATA WIKI - Big Data IG

What is Big Data?

Big data is a term that describes the large volume of data – both structured and unstructured – that inundates 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 that lead to better decisions and strategic business moves.

The use of Big Data is becoming common these days by the companies to outperform their peers. In most industries, existing competitors and new entrants alike will use the strategies resulting from the analyzed data to compete, innovate and capture value.  

Big Data helps the organizations to create new growth opportunities and entirely new categories of companies that can combine and analyze industry data. These companies have ample information about the products and services, buyers and suppliers, consumer preferences that can be captured and analyzed.

While the term “big data” is relatively new, the act of gathering and storing large amounts of information for eventual analysis is ages old. The concept gained momentum in the early 2000s when industry analyst Doug Laney articulated the now-mainstream definition of big data as the three Vs:

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. The name 'Big Data' itself is related to a size which is enormous. Size of data plays very crucial role in determining value out of data. Also, whether a particular data can actually be considered as a Big Data or not, is dependent upon volume of data. Hence, 'Volume' is one characteristic which needs to be considered while dealing with 'Big Data'.

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.

The term 'velocity' refers to the speed of generation of data. How fast the data is generated and processed to meet the demands, determines real potential in the data.

Big Data Velocity deals with the speed at which data flows in from sources like business processes, application logs, networks and social media sites, sensors, Mobile devices, etc. The flow of data is massive and continuous.

Variety. Data comes in all types of formats – from structured datasets (examples can be seen , & ), numeric data in traditional databases to unstructured text documents, email, video, audio, stock ticker data and financial transactions. Variety refers to heterogeneous sources and the nature of data, both structured and unstructured. During earlier days, spreadsheets and databases were the only sources of data considered by most of the applications. Now days, data in the form of emails, photos, videos, monitoring devices, PDFs, audio, etc. is also being considered in the analysis applications. This variety of unstructured data poses certain issues for storage, mining and analysing data.

Benefits of Big Data Processing

Ability to process 'Big Data' brings in multiple benefits, such as-

  • • Businesses can utilize outside intelligence while taking decisions
  • Improved customer service
  • Early identification of risk to the product/services, if any
  • • Better operational efficiency

Why is Big Data Important ?

The importance of big data does not revolve around how much data a company has but how a company utilises the collected data. Every company uses data in its own way; the more efficiently a company uses its data, the more potential it has to grow. The company can take data from any source and analyse it to find answers which will enable:

  1. Cost Savings : Some tools of Big Data like and Cloud-Based Analytics can bring cost advantages to business when large amounts of data are to be stored and these tools also help in identifying more efficient ways of doing business.
  2.  Time Reductions :The high speed of tools like Hadoop and in-memory analytics can easily identify new sources of data which helps businesses analyzing data immediately and make quick decisions based on the learnings.
  3.  Understand the market conditions : By analyzing big data you can get a better understanding of current market conditions. For example, by analyzing customers’ purchasing behaviors, a company can find out the products that are sold the most and produce products according to this trend. By this, it can get ahead of its competitors.
  4.  Control online reputation: Big data tools can do sentiment analysis. Therefore, you can get feedback about who is saying what about your company. If you want to monitor and improve the online presence of your business, then, big data tools can help in all this.
  5. Using Big Data Analytics to Boost Customer Acquisition and Retention

    The customer is the most important asset any business depends on. There is no single business that can claim success without first having to establish a solid customer base. However, even with a customer base, a business cannot afford to disregard the high competition it faces. If a business is slow to learn what customers are looking for, then it is very easy to begin offering poor quality products. In the end, loss of clientele will result, and this creates an adverse overall effect on business success. The use of big data allows businesses to observe various customer related patterns and trends. Observing customer behaviour is important to trigger loyalty.

  6. Using Big Data Analytics to Solve Advertisers Problem and Offer Marketing Insights

    Big data analytics can help change all business operations. This includes the ability to match customer expectation, changing company’s product line and of course ensuring that the marketing campaigns are powerful.

  7. Big Data Analytics As a Driver of Innovations and Product Development

    Another huge advantage of big data is the ability to help companies innovate and redevelop their products.

  8.  

Best Examples Of Big Data

The best examples of big data can be found both in the public and private sector. From targeted advertising, education, and already mentioned massive industries (healthcare, insurance, manufacturing or banking), to real-life scenarios, in guest service or entertainment.  by the year 2020, 1.7 megabytes of data will be generated every second for every person on the planet, the potential for data-driven organizational growth in the hospitality sector is enormous.

Big data can serve to deliver benefits in some surprising areas.

Big Data in Education industry

Following are some of the fields in education industry that have been transformed by big data motivated changes

  • Customized and dynamic learning programs:
  • Reframing course material:
  • Grading Systems:
  • Career prediction:

Big Data in Insurance industry

The insurance industry holds importance not only for individuals but also business companies. The reason insurance holds a significant place is because it supports people during times of adversities and uncertainties. The data collected from these sources are of varying formats and change at tremendous speeds.

Collecting information

As big data refers to gathering data from disparate sources, this feature creates a crucial use case for the insurance industry to pounce on. Eg: When a customer intends to buy a car insurance kenya, the companies can obtain information from which they can calculate the safety levels for driving in the buyer’s vicinity and his past driving records. On basis of this they can effectively calculate cost of car insurance as well.

Gaining customer insight

Determining customer experience and making customers the center of a company’s attraction is of prime importance to organizations.

Fraud detection

Insurance frauds are a common incidence. Big data use case for reducing fraud is highly effective.

Threat mapping

When an insurance agency sells an insurance, they want to be aware of all the possibilities of things going unfavourably with their customer, making them file a claim.

 

Big data in Government industry

Along with many other areas, big data in government can have an enormous impact — local, national and global. With so many complex issues on the table today, governments have their work cut out trying to make sense of all the information they receive and make vital decisions that affect millions of people. Governments, be it of any country, come face to face with a very huge amount of data on almost daily basis. Reason being, they have to keep track of various records and databases regarding the citizensThe proper study and analysis of this data helps the Governments in endless ways. Few of them are:

Welfare schemes:

Cyber security:

PDF - Big Data Applications in the Government Sector: A Comparative Analysis among Leading Countries

Big Data in Banking Sector

The amount of data in banking sectors is skyrocketing every second. According to GDC prognosis, this data is estimated to grow 700% by 2020.

study and analysis of big data can help detect -

  • The misuse of credit cards
  • Misuse of debit cards
  • Venture credit hazard treatment
  • Business clarity
  • Customer statistics alteration
  • Money laundering
  • Risk Mitigation

 

Real-Time Big Data Analytics Tools

 

More and more tools offer the possibility of real-time processing of Big Data.

Storm

Storm, which is now owned by Twitter, is a real-time distributed computation system.

Cloudera

Cloudera offers the Cloudera Enterprise RTQ tools that offers real-time, interactive analytical queries of the data stored in HBase or HDFS.

Gridgrain

GridGain is an enterprise open source grid computing made for Java. It is compatible with Hadoop DFS and it offers a substitute to Hadoop’s MapReduce.

SpaceCurve

The technology that SpaceCurve is developing can discover underlying patterns in multidimensional geodata.

 

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