9 Key Reasons Causing Big Data Need

Data is facts and statistics collected together for reference or analysis. Big data is extremely large data sets that may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions. There are several technologies used for handling big data.

In this article we are going to discuss top 9 reasons which caused need for big data.

1. Huge growth in data since last couple of years:

With social media, digital devices and many technology awareness innovation, data is rapidly increasing.

According to Forbes, Over the last two years alone 90 percent of the data in the world was generated.

2. Unstructured data is more:

Structured data refers to any data that resides in a fixed field within a record or file. This includes data contained in relational databases and spreadsheets.

Unstructured data usually refers to information that doesn't reside in a traditional row-column database.Its exactly opposite of Structured data. Unstructured data files often include text and multimedia content.

Examples of unstructured data include e-mail messages, word processing documents, videos, photos, audio files, presentations, webpages and many other kinds of business documents.

Around 80% of the data is unstructured or exists in widely varying structures which are difficult to analyze.

3. For large quantities Structured data format has limitations:

Structured formats have few limitations with respect to handling large quantities of data. Structured databases were not designed to cope with the scale and agility challenges that face modern applications, nor were they built to take advantage of the commodity storage and processing power available today.

4. Challenges in integrating distributed information:

Data integration involves combining data residing in different sources and providing users with a unified view of them. This process becomes significant in a variety of situations, which include both commercial and scientific domains. Data integration appears with increasing frequency as the volume and the need to share existing data explodes.

As a summery, it is difficult to integrate information distributed across multiple systems.

5. Lack of clarity on which data to be analysed:

It is challenging to understand which data will be useful for business. It is really confusing to business people as market is dynamic and data statistics are changing every other day.

Most business users do not know what should be analyzed.

6. Valuable data is dormant or discarded:

With the time, mostly valuable data is getting discarded or dormant.

We can understand it like data is going to asleep for long time if its not considered valuable. Sometimes it may also happen that due to deep sleep of such data, entire stream of data will vanish for longer period or will not grow.

7. Expensive to integrate large volumes of unstructured data :

With volume of unstructured data, the integration becomes complex. It is too expensive to integrate large volumes of unstructured data.

As we see importance of unstructured data there is a need for better solutions to use it.

8. Useful lifespan of much information is short:

Information is dynamic, it keep on changing with time and innovation. There are stages where it is not recognized as well.

Everything has birth and death - same goes with information if its not retained or thrown in long sleep being not useful.

A lot of information has a short, useful lifespan.

9. Information need context:

Context is the circumstances that form the setting for an event, statement, or idea, and in terms of which it can be fully understood. It is important to have context in place as it adds meaning to the existing information. Otherwise information is no more information. Its just going to be meaningless data.

All these are reasons why there is need for Big Data. Hadoop is one of big data popular technology now days - which is a free, Java-based programming framework that supports the processing of large data sets in a distributed computing environment. It is based on Google File System (GFS). In upcoming few articles, we will go deeper into Big Data.

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