Big data is a big word in town. Of course, why not when 500 million tweets are sent per day. And 172,800,000 transaction are handled by visa per day. So, do you want to become part of the game and get a big data job? Well, then you need to learn some big data skills.
It is said that “Numbers have an important story to tell. They rely on you to give them a voice.” Therefore, be prepared to learn the skill sets listed below to join the band of data scientists and data analysts.
But before that,
How does Big Data Impact your Business?
In three ways,
- Your business will generate huge amounts of data. And these data vary from user behavior, purchases, and traffic. Therefore, if you want to improve your business performance, you can use the client data to study patterns.
- You can provide custom-based services to clients by studying client data. Moreover, you will be able to provide market-specific services to clients and improve delivery.
- You can process large amounts of data to identify hidden patterns and correlations. Eventually, the results produced will affect the production, services, distribution and workforce levels.
Significantly, with such immense benefits with big data your skills will put you on the right job track.
Big Data Skills to Get you Hired in 2019
NoSQL technologies (e.g. Cassandra and MongoDB)
NoSQL databases can store volumes of structured, semi-structured and unstructured data. Some important databases are,
This is a column-oriented NoSQL database. It is good for applications with optimized read and range based scan.
This is a highly scalable database. It requires minimal administration and has no single point of failure. Moreover, it is good for applications with fast and random, read & writes.
This is a document-oriented NoSQL database which is schema free. Furthermore, it gives full index support for high performance and replication for fault tolerance.
Python Programming, important among big data skills
Python is easy to learn due to its easy syntax and good community support. Moreover, python has a wide set of data libraries and integrates easily with web applications. Therefore, this is important among big data skills.
Furthermore, with Python, you can build scalable applications that helps process large data sets.
This is important among the programming languages. In order to work with large datasets, programming with Java is required. Java Virtual Machines (JVM) are used to run operations in the big data ecosystem.
Java is core among the big data skills.
R Programming, vital among big data skills
R Programming is used to visualize and analyze data. Data mining and statistical computing find applications of R in creating reports. It is important among big data skills.
Significantly, it is supported by the R Foundation and is helpful in creating graphics for data analysis.
SAS (Statistical Analysis System)
SAS provides you solutions of high quality. Distributed processing of data is faster using SAS and you get quick insights.
This is essential among big data skills. This is an open source cluster computing software framework. You can store large amounts of data with fast processing.
Moreover, it can handle multiple requests at the same time. This enables you to deliver insights. It provides flexibility for processing unstructured data and has high scalability.
Apache Hive, vital among big data skills
This is an open source data warehousing language to analyze data in the Hadoop system. And important among big data skills.
Furthermore, it has an SQL-like interface to query data stored in the database. Significantly, Hive has three main functions namely, data summary, query
MapReduce is used to write applications to process large structured and unstructured data.
Correspondingly, MapReduce has two main functions. The Map function forms a master node that takes inputs and distributes work to other nodes in a cluster. Concurrently, after the processing is complete, it needs to form a report.
On the other hand, the Reduce function takes the output and reduces the results from all nodes into a report or query.
Pig is an open course platform for processing the data stored in the Hadoop ecosystem. It has an inbuilt compiler for MapReduce programs to perform data extraction.
Significantly, Pig Latin language is used to execute tasks in the Hadoop file system.
It is a fast, in-memory data processing engine with multi-program APIs. Furthermore, the languages can be in Java, Python, Scala.
Moreover, it also has libraries that enable it to manage tasks for SQL, machine learning and data streaming.
Spark is also called as data access engine. Spark produces faster data processing using distributed systems along with cluster managers.
Data conveyed in graphical or pictorial format will be highly beneficial. It can also convey concepts is an easy manner.
Product/service-oriented companies use data visualization for decision making. Furthermore, it helps to identify areas for improvement.
Machine Learning is a set of algorithms that can learn from data. Eventually, these methods help to identify hidden patterns and correlations in datasets.
Significantly, these algorithms can process
Big data technologies are vital for the overwhelming success of your company. It will be better if you get
In these institutes, you will get first-hand knowledge about data structures, big data analytics, analytical skills, big data tools, and other data sciences information.
Remember, “Turning Data into Information and Information into Insight” is what drives the socio-economic world. You can be part of this change by taking immediate steps to enroll in a good training institute.