All About BIG DATA

With time the generation of the data has also increased and tackling such a huge amount of data has also become a challenge. The need to use and analyze data efficiently has become essential. Here comes the concept of Big Data, one of the most favourable technologies of the decade. Today, Big Data has become a priority for technical experts and data analysts as their primary job. They collect large data and form figures and reports for easy perusal of the data. Hence, it has become important to learn about Big Data in the technology world.

Big Data refers to the vast amount of unstructured data that business processes create. It is usually the large amounts of data from the websites, transactions, emails, etc. On the basis of the data form in which it is stored, the data is categorized into three forms:

1) Structured Data – Data accessed, processed, and stored in a fixed format or form is called structured data.

2) Unstructured Data – Data without any structure or a specific form is called unstructured data.

3) Semi-structured Data – This kind of data contains a combination of both structured and unstructured data.

The main characteristics are specified by the 5 Vs, these are Volume, Velocity, Value, Variety and Veracity. With the new digital trends, a lot of changes take place in the industry in consumer behavior creating an enormous amount of data. This is the reason why every business wants employees to learn Big Data to make use of this data. It will help them reach consumer insights and inputs for their business. The key benefits that Big Data offers for companies today are:

1)Time-Saving

2)Cost Saving

3)Customer Service

4)Consumer Insights

5)Relevant and Trustworthy

6)Security

7)Operational Efficiency

8)Real-time Monitoring

9)Risk Identification

10)Predictive Analysis

The presence of Big data is everywhere in this highly digital world. The Internet of Things (IoT) has given rise to new data sources. Now every item is digital, and new data keeps flowing to the company with these items. This huge amount of data we produce and access every day is nothing but Big Data. No industry is untouched by Big Data, and so it becomes important to learn about Big Data.

There has been a huge increase in the funding available for the Big data field. Many venture capital firms are investing in start-ups worldwide. The governments are spending on R & D in this field.

Most Trending Big Data Technologies

Companies are investing a huge amount in big data technologies, and the big data market is continually growing. Big data and analytics have become mainstream now in the IT world. The maximum growth is spending on banking, insurance, investment services and the healthcare industry. The most popularly adopted technologies include data analytics and its application in risk management, fraud detection, and customer service. The trending technologies include the following:

1) Hadoop Ecosystem

Apache Hadoop is the most common and popular Big Data technology used worldwide. Hadoop-based products are growing in number, and many vendors support the Hadoop ecosystem.

2) Apache Spark

Spark is another part of the Hadoop ecosystem independently used everywhere. Spark is the processing engine for Big data in Hadoop, and it is faster than the Hadoop engine. It is written in Scala, JAVA, Python, and R. 

3) NoSQL Databases

These are the special databases that specialize in unstructured data usage and storage. The popular databases are MongoDB, Cassandra, etc. These are known for fast performance.

4) Python

Python provides a huge number of libraries to work on Big Data. You can also work – in terms of developing code – using Python for Big Data much faster than any other programming language. These two aspects are enabling developers worldwide to embrace Python as the language of choice for Big Data projects.

5) Apache Kafka

Apache Kafka is a distributed streaming platform. It is developed by Apache Software Foundation in the year 2011. It is written in Scala, JAVA.

6) Blockchain

The major capabilities of blockchain are shared ledger, smart contracts, privacy and consensus. Shared ledger append-only distributed system of records across a business network. Smart contracts in business terms are embedded in the transaction database and executed with transactions. The major features of privacy are ensuring appropriate visibility and making the transaction secure authenticated and verifiable. The consensus in business environments all parties can agree to a network verify transactions using blockchains.

7) Airflow

Apache Airflow is a workflow automation and scheduling system that can be used to author and manage data pipelines. It uses workflows made up of DAGs or in short Directed Acyclic Graphs of a particular task. Airflow is used in defining workflows in the form of the code so as to provide easier maintenance, testing and versioning.  It is written in Python programming language.

8) Predictive Analytics

This technology involves the use of data mining and modeling along with machine learning to predict future behaviors or events. This is widely common in marketing, finance, credit score, fraud detection, etc.

9) Prescriptive Analytics

This part of data analytics helps in offering advice to the companies regarding what and how should they do for desired results.

10) Data Lakes

The organizations are creating huge repositories for collecting data from different sources and storing it in its natural state. These are the Data Lakes. They let the organizations store the data when the organizations are using the data.