Tools that automate Big
 Data !

Have you ever given a serious thought on what it actually takes to be in the fastest growing profession or what new skills you have to pick up to prepare yourself for the hottest career of the 21st century! Well, all you need is the super power of Data Science and a magical wand that will let you do some technical tricks! For that, we will help you by giving you the dynamism on the Data Science and Big data libraries, frameworks, databases and technical and analytical tools! Have a quick overview of the great tools for Big Data and Data Science, that will help you dice your career as Data Analyst.

1.RStudio

Do you know why R is the most widely preferred by Statisticians and Data Analysts? It is simply because of having a wide variety of build-in statistical commands and packages to handle the huge volumes of data and consists of powerful functions to tackle the different nature of issues related to Big Data processing. R is especially designed and developed for Data Analysts, Scientists, Data Engineers, Statisticians and Researchers, to let them integrate their Big Data workflows with the analytical tool.

2. Hadoop

Like we know in every minute around 2.5 quintillion bytes of data is created, which triggers the need to stored at a more rapidly! And this where Hadoop steps in! Hadoop is an open sourse framework that allows you to store and process huge volumes of data quickly. It provides massive storage space for all kinds of data while also storing multiple copies of all data automatically. It also powers you to process tasks simultaneously, while also offering more flexibility to collect, process and analyze data from the various forms of structured and unstructured data.

3. MongoDB

Since data is being generated in great velocity, it is undoubtedly the MongoDB is the most prefered choice for extracting data and creating business values and solutions. It is due to its key characteristics of being flexible, faster and scalability. Mongo is basically a NoSQL database, which is designed to enhance existing RDBMS systems by storing records as documents and to power the online, off-line and real-time operational applications with greater ease to help end users and business outcomes.

4. Spark

Well, unlike MongoDB, Spark is from SQL family, that provides a MapReduce solution and a complete set of tools for managing big data processing, while supporting SQL queries, streaming data, machine learning and graph data processing. It is an open source big data processing framework developed as an alternative to Hadoop, to boost speed and performance and ease of use. Spark is a simple yet powerful all-in-one solution to manage different bigdata applications

5. Zoho Analysis

Zoho is another data analytic tool, which is reshaped into a robust self-service business intelligence, data analytics and an online reporting platform. The software is upgraded to boost industrial performance by consolidating data from different sources. Un line the other analytical tools, it is used to resolve hidden insights, trends and to monitor business metrics and outcomes. Zoho is flexible and offers seamless data gathering, powers visualization, simplifies creation of charts and supports on-premise deployment.

6. Tableau

Like Zoho, Tableau is another simple yet powerful Big data analytics tool that helps to make more informed decisions faster by transforming data into actionable insights. Unlike other analytic tools, Tableau allows a single interface for all data, regardless of where it is stored. It is considered as one of the fastest evolving Business Intelligence (BI) and Data Visualization tool, for its factors like fast to deploy, easy to learn and user-friendly

7. Neo4J

Neo4J is basically an open-source graph database used to analyse complex networked information. Well it is primarily designed to capture relationship between graph and data. Database like Neo4J is mainly used for social softwares. Unlike other graph databases, Neo4j solves analytical problems with ease, where others struggle to solve in a flexible way

With these tools learn how to slice and dice large data and convert them into more meaningful visualizations through graphs, charts and dashboards. Become proficient in Big Data analysis!