Application of Big Data Across Different Sectors

Technology has come to the horizon of developing intelligent automatons. This has become possible owing to huge developments in technology infrastructure and information. One such modern development is Big Data. Big Data is a field that treats extremely large datasets for better analytics and computational results. It is already on its way to transforming a number of sectors linked to people’s lives.

Source : Application of Big Data Across Different Sectors

Big Data in the Government sector

The government of a country has voluminous data on its citizens, topography, mineral wealth, unemployment, and more. Governments across the globe use this data to make policies for its citizens, and scientific methods like Big Data analytics come a long way in helping them with the same.

• The government makes use of Big Data to create welfare schemes that will turn out to be effective after they are operational. To develop such schemes, the government relies on the data it has collected from people and other sources on a number of fields.
• The cyber threat prevention agencies rely on Big Data to recognize loopholes in the digital setup and hence prevent data theft. Moreover, tax evaders can be tracked using Big Data findings.

Big Data in Media and Entertainment industry

The rise of social media platforms has given a new aspect to communication. Almost every person that possesses a smartphone casts his/her social footprint on the web, which in turn is stored on the servers and hence contributes to creating a database.

• The media and entertainment industry can predict user interests and hence steer in the direction of creating popular media projects.
• Big Data helps in pinpointing animosities and get a visual insight if audience reviews.
• Big Data can help the advertisement industry to target a specific audience based on the data analysis.
• Example: Spotify provides auto-suggestions and music recommendations to users on the basis of analyzed data collected from users all over the world.

Big Data in Weather Forecasting

Weather forecasting agencies and other big corporations across the world rely on data collected from a number of satellites to predict accurate weather for different regions. Accurate weather forecasts help in making necessary preparations for times of crises. Moreover, natural disaster patterns and freshwater statistics can also be deduced from the images provided by satellites.

Big Data in Banking Sector

The data stored by banks is to grow by 700% by 2020 according to a study conducted by GDC prognosis. It turns out to be Big Data literally and otherwise. This data can be used for tweaking key banking operations for better security and customer interaction.

• Big Data can help to curb the misuse of credit and debit cards
• Big Data provides business clarity to the leading management of a bank.
• It may help to mitigate the financial risks when analyzed effectively.

Billy Mark is a Microsoft Office expert and has been working in the technical industry since 2002. As a technical expert, Billy has written technical blogs, manuals, white papers, and reviews for many websites such as office.com/setup.

Complete Guide to Big Data and HDFS

The world is getting a huge amount of data every day from various sources like social media, authentication and user-generated data. The tradition means are enough compatible to process it. The traditional database management system is also inefficient to manage it effectively.

Source : https://manage-offiice.com/complete-guide-to-big-data-and-hdfs/ 

SQL and RDMS are unable to cater the problem so we need a new kind of architecture and processing device that can able to manage the huge amount of data. Big data is going to be the subject of future and the amount of data will increase by many folds in near future.

Before moving to handle the big data we should know what big data is first!

Big data is the collection of huge amount of data which are not able to process with the traditional way of computing technique. The amalgam of many tools and techniques and business model are needed to store and process it.

Now the question came that which kind of data is big data?

• Data store by the black box of the airplanes, helicopter, and fighter planes etc comes under it. It contains various kind of information like image, sound, video capturing, conversation, statistics of the various machines etc.
• Data on social media platform which includes pictures, video, chats, and user-generated data etc.
• The data store during the trading in a stock exchange, companies share price, their trading pattern and shares valuation-devolution etc.
• Energy generation centers, power distribution centers, grids are generating bulk amount of data related to the transmission, distribution and many other aspects of gridding.
• Data generated by web browsers are enormous, so it also came under the category of big data.

 Kind of Big Data

 It could we be divided into three basic categories first is structured data, second is semi-structured data and the third one is unstructured data.

1. The data which related each other and establish any kind of relation is called relational or structured data.
2. Data which can relate a fragment of other data is called semi-structured data. Data generated in XML form come under it.
3. Data which do not relate to a different kind of data is called unstructured data. Word documents, picture, statistic or log file, PDF come under unstructured data type.

If the huge amount of data is difficult to process then why is it so important?

The huge amount of data becomes very productive and path-breaking for any company after processing. These data contain the census, complain, opinion and reaction which can be a decisive factor in the growth of any industry.

Social media comments, a reaction is creating a trend, so it plays an important role in the business development plan and product promotion strategy of any company.

Problems associated with big data

Storing of data, processing data, transferring data, presenting, fetching the desired piece of data are the common problem associated with big data.

1. HDFS (Hadoop distributed file system)

1It is the storage structure for big data. It fragments the data into a smaller unit and store at “Slave node”. A root node on more reliable hardware stores all information about the slave nodes. Each slave node has multiple copies of it and if once failed the responsibility of processing sifted to another. In this way, each set of information is processed individually and sends its report to the client directly.

2. MapReduce

 It is the processor of HDFS structure that is solely responsible for the processing of data at each slave node and aggregation of the fragmented data at reducer and giving output in a user understandable form.

3. YARN

 It is responsible for the scheduling and maintaining the productivity of the slave node. It is the one which allots the time slice to every single node to process. It seems that every node it operating simultaneously but due to time slice that allotted to every single node each node works one by one but with tremendous speed .so yarn is called the mind of HDFS.

4. PIG

PIG works as the support system of Map reduces. Actually, the PIG is extracting, developing and processing data inside the MapReduce. It can process all kind of data.

Billy Mark is a Microsoft Office expert and has been working in the technical industry since 2002. As a technical expert, Billy has written technical blogs, manuals, white papers, and reviews for many websites such as office.com/setup.