Big data tools must through for 2019
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In this blog, you have many articles regarding what is big data? What big data does. And also the advantages of it. This big data is not a single platform. This is a platform where multiple tools work above the big. so it means, on the top of big data, we do have many tools.  Each tool is different from one another and has a unique advantage when compared to the other. So for the person in the It industry, there are some top Big data tools must through for 2019. It means, this article explains what you must prepare and be thought to become a successful data analyst in the IT industry.

In the IT market, the pay for the big data analyst is more.  The fresher salary usually starts from 5 LPA. And the scientist was working more and more to build much and more tools on the top of the big data. So let us have looked over the top 10 big data tools must through for 2019.

Big data tools must through for 2019?

All the big data tools 2018 have high demand in the IT market. So among BA big data tools and technologies in the IT market, we must be through with some tools.

Kafka :

Apache Kafka is a tool to handle a large amount of rapid data. This handling is done using the relatively modest set of hardware. It is basically used to create a subscription model functionality. On the basis of a large amount of data, it allows asynchronous messaging. As per the LinkedIn observation, it can process one trillion events per day. In a fault tolerant manner, it can generate messages for fault tolerant consumption. Kafka is a powerful and useful tool to maintain large messaging channels.

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Cloudera :

Cloudera is the first company to offer the Hadoop distribution. The major idea is to set up and easily manage their Hadoop clusters. Basically, Cloudera is an excellent tool to offer the comprehensive console. This usually gives the insights of all the Hadoop clusters. Additionally, it supports node js feature. It means instead of starting from scratch, to deploy a particular node configuration, we can create a template and can reuse it to create more nodes. In all Hadoop installation, Cloudera is an excellent tool for security and stability.

Splunk :

It is another powerful data aggregate and analyzer tools to gather an excessive amount of data in real time. Additionally, it can generate insights in the form of reports and dashboards. It is used in analyzing machine-generated big data like logs, error reports as well as the status reports.  This tool is advantageous to the organizations, it can be used in the areas of application management, security and compliance to process the logs.

Elastic  search :

Elastic search is a search engine that allows the system to index and find a file in real time. It allows organizations to quickly set up fast and reliable functionality. Its major intentions are to implement full-text search,  autocomplete supported search, fuzzy search and also the document-oriented search. This document-oriented search has a powerful impact on finance and legal firms. Here, massive amounts of historical records can be accessed to generate search results quickly. Additionally, this can also work on the multi-tenant system. This makes cost-effective to set up address uses working on different installations (or) versions of the same master system.

Flume :

The Hadoop file system is an excellent tool for running map reduce jobs to process the excessive amount of data. But in real time application, a proper tool is needed to collect, aggregate and transport. And flume is an excellent tool in this category. Additionally, flume also maintains a steady flow of data between the ingesting and persisting operations.

Like there are some other tools of big data, that you must need to know. And the above mentioned were the topmost tools. So have look over the demo Big data Hadoop online training

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In order to start learning Big Data has no prior requirement to have knowledge on any technology required to learn Big Data Hadoop and also need to have some basic knowledge of java concept.  It’s good to have knowledge of Oops concepts and Linux Commands

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