Big Data and the Tools Used

 In our traditional approaches, the datasets or data are stored in Relational Database Management System (RDBMS).

As the data produced due to the use of social media sites have become larger, the time to process the data, data cost and storage space becomes insufficient.

Overcoming these limitations, big data came into the picture.

Therefore, the goal of big data systems is to surface connections from a large volume of heterogeneous data.

What is big data?   

The enormous quantity or volume of data is called "Big data". It is the complex and unprocessed data (in exabytes or zeta bytes). Using traditional methods, they are difficult to process.

Characteristics of Big data:

The definitions of 3 major V’s of big data are:

1. Volume:

The datasets can be orders of magnitude larger than traditional datasets.

2. Velocity:

Another way in which big data differs from other datasets is the speed that information moves from through the system.

3. Variety:

The formats and types of data can vary significantly and big data handles it regardless of its sources.

TOOLS OF BIG DATA:

The big data tools are Hadoop, Hive, Sqoop, HBase, Pig, etc. They are used to analyse and process the data based on their need.

APPLICATIONS OF BIG DATA:

Some of the real-time examples are:

•       Personalized health plans for cancer patients

•       Real-time data monitoring and cyber security protocols

•       Personalized marketing.

•       Fuel optimization tools for the transportation industry.

•       Monitoring health conditions through data from wearable.

•       Live road mapping for autonomous vehicles.

BIG DATA LIFE CYCLE:

The general categories involved with big data processing are:

1.    Ingesting data into system:

 

Data ingestion is the process of taking raw data and providing it to the system. The complexity of this operation depends heavily on the format and quality of the data sources and how far the data is from the desired state prior to processing.

Tool used: Apache Sqoop

 

2.  Persisting the data in storage:

 

The ingestion processes typically provide the data to the components that manage storage system. While this seems like a simple operation, the volume of incoming data, the requirements for availability, and the distributed computing layer make more complex storage systems necessary.

Tool used: Apache Hadoop’s HDFS

 

3.  Analysing and computing data:

 

The computation layer is perhaps the most diverse part of the system as the requirements and best approach can vary significantly depending on what type of insights desired.

Tool used: Apache Hadoop’s Mapreduce

 

4.  Visualizing the results:

Due to the type of information being processed in big data systems, recognizing trends or changes in data over time is often more important than the values themselves. Visualizing data is one of the most useful ways to spot trends and make sense of a large number of data points.

Tool used: Apache Pig

 

Therefore, in conclusion, big data systems are uniquely suited for surfacing difficult-to-detect patterns and providing insight into behaviours that are impossible to find through conventional means. By correctly implementing systems that deal big data organisations can gain incredible value from the data that is already available.

Comments

Post a Comment

Popular posts from this blog

Natural Language Processing

                                              NLP in Digital Marketing What is NLP? Natural language processing or NLP is a sub ordinate of computational linguistics and machine learning. It connects computer data with human language. This technology interprets human language, text, voice, emotions into computer programmatic for making the work of computer easy to provide better results to the user. It has various fields to coordinate with the user like voice recognition, semantic search, sentiment analysis, optical Character recognition etc. Impact of NLP on digital marketing The retail industry is undergoing tumultuous changes with the stream of technology. In the previous few decades, the inclination of digital marketing hick unto its pick. This is because people are increasingly involving into technical devices for their needs. Hence digital marketing and NLP ...
Read more

5 Reasons why SEO is the feasible digital marketing tool

Image
  What we seek, we shall find! But we need the light to guide. And that, my associates, is what SEO does. It is the light that guides. To start with, SEO stands for Search Engine Optimisation, the process of modifying the website design and content to help it appear in search engines. Now, how does this help in reaching people? What do we do if we wish to buy or know something about which is best? We seek the know-it-all's help and begin to type in the lengthy white tab on our mobile or computer screen like, "Top 5 Air Conditioners" "Best TV's under 30000" "How to start up a new business" Google then shows up the results which it thinks would suit our needs based on the keywords we used. This is where SEO comes into play . This SEO is the one which makes the Google think that a particular site fits our need. The sites use the SEO to make Google understand what their content is about. So, everytime someone searches with keywo...
Read more
Image
  Customer Segmentation as an Invaluable factor in Marketing Consumers are the main source of sustenance for any business organization. Keeping them satisfied and meeting their renewed needs helps the business grow. Since the customers are people with heterogeneous demands the necessities, they require changes from person to person. Satisfying everyone together is not a simple process, as a result they need to be divided into groups based on similar characteristics. This is known as Customer Segmentation. The prospective customers are divided into segments based on similarities. This division is made based on the needs, age, income, family size, gender, geography, demands, consumption, spending, lifestyle and shopping behaviors. The identification of ideal customers leads to grouping them into potential segments or existing segments that allow the organizations to focus on providing better services. Significance of Customer Segmentation Customer Segmentation helps Business ...
Read more