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Tag: big data certification courses

The Growing Need of Data Storytelling as Salient Analytical Skill!

Posted on by Imarticus Learning

Data storytelling is a methodology used to convey information to a specific audience with a narrative. It makes the data insights understandable to fellow workers by using natural language statements & storytelling. Three key elements which are data, visuals, and narrative are combined & used for data storytelling.

The data analysis results are converted into layman’s language via data storytelling so that the non-analytical people can also understand it. Data storytelling in a firm keeps the employees more informed and better business decisions can be made. Let us see more about how data storytelling is an important analytical skill & how it will help in building a successful Big Data Career.

Benefits of Data Storytelling

The benefits of data storytelling are as follows:

  • Stories have always been an important part of human civilization. One can understand the context better via a story. Complex data sets can be visualized and then data insights can be shared simply through a story to non-analytical people too.
  • Data storytelling helps in making informed decisions & stakeholders can understand the insights via Data storytelling and you can compel them to make a decision.
  • Data analytics is about numbers and insights but with data storytelling, you make your data analytics results more interesting.
  • The risks associated with any particular process can be explained to the stakeholders, employees in simple terms.
  • According to reports, more data is produced from 2013 than produced in all human history. To manage this big data and to make data insights accessible to all, data storytelling is a must.

Tips for Making a Better Data Story 

  • If you are running an organization, make sure to involve stakeholders/investors in data storytelling. This helps in increasing clarity in communication and they do not find a lack of information.
  • Make sure to embed numerical values with interesting plots for a data story. Our brains are designed to conceive visual information faster. Only numerical insights will make the data story boring and more complex to understand. The data insights should be conveyed in a layman’s language through a data story.
  • Data visualization should be used for data storytelling but it should not hide the critical highlights in the data set.
  • Make sure you imbibe all the three aspects of data storytelling which are visuals, data & narrative. The excess of any attribute can hamper the effectiveness of your data story.
  • The outliers/exception in the data set should be analyzed and included in your data story.

The Growing Need for Data Storytelling 

New ways of data analytics like augmented analysis, data storytelling, etc. are surging a lot in recent days due to the high rate of data production by firms/businesses. One can learn analytical skills from a Data Analytics course from Imarticus Learning. To build a successful Big Data Career, you will need to learn these new concepts in data analytics.

big data analytics courses in IndiaConclusion 

Imarticus Learning is one of the leading online course providers in the country. You can learn key skills via a Data Analytics course from industry experts provided by Imarticus Learning. Start learning data storytelling now!

What makes Hadoop so Powerful and how to Learn it?

Posted on by Imarticus Learning

Why Hadoop?

With today’s powerful hardware, distribution capabilities, visualization tools, containerization concepts, cloud storage and computing capabilities, huge amounts of raw data can be stored, processed, analyzed, and converted into information, used for decision making, historical analysis and for future trend prediction.

Understanding Big data and converting into knowledge is the most powerful thing any entity can possess today. To achieve this, Hadoop is currently the most used data management platform. The main benefits of Hadoop are:

  1. Highly scalable
  2. Cost-effective
  3. Fault-tolerant
  4. Easy to process
  5. Open Source
  1. What is Hadoop?

Hadoop is a Highly distributed file system (HDFS), maintained by Apache Software Foundation. It is a software to store raw data, process it by leveraging the distributed computing capability and to manipulate and filter it for further analysis.

Several frameworks and machine learning libraries like python and Operate on the processed data to analyze and make predictions out of it. It is a horizontally scalable, largely distributed, clustered, highly available, and reliable framework to store and process unstructured data.

Hadoop consists of the file storage system (HDFS), a parallel batch processing engine Map Reduce and a resource management layer, YARN as standalone components. Open source software like Pig, Flume, Drill, Storm,Spark, Tez, Hive, Kafka, HBase, Mahoot, Zepplin etc. can be integrated on top of the Hadoop ecosystem to achieve the intended purpose.

How to Learn Hadoop?

With interest in Big Data growing day by day, learning it can help propel your career in development. There are several Big data Hadoop training courses and resources available online which can be used to master Hadoop theoretically.

However, mastery requires years of experience, practice, availability of large hardware resources and exposure to differently dimension ed software projects. Below area few ways to speed up learning Big Data.

  1. Join a course: There are several Big Data and Hadoop training courses available from a developer, architect, and administrator perspective. Hadoop customization like MapR, Horton Works, Cloud era etc. offer their own certifications.
  2. Learning marketplaces: Virtual classrooms and courses are available in Course Era, Udemy, Audacity etc. They are created by the best minds in the Big Data profession and are available at a nominal price.
  3. Start your own POC: Start practice with a single node cluster on a downloaded VM. Example: Cloud Era.com quick start.
  4. Books and Tutorials on the Hadoop ecosystem: Hadoop.apache.org, Data Science for Business, edurekha,digital vidya, are a few examples apart from the gazillion online tutorials and videos.
  5. Join the community: Joining the big data community, taking part in discussions and contributing back is a surefire way to increase your expertise in big data.

Points to remember why Learning Hadoop:

Below are the things to keep in mind while working on large open source Big Data projects like Hadoop:

  1. It can be overwhelming and frustrating: There will always be someone wiser and more adept than you are.Compete only with yourself.
  2. Software changes: The ecosystem keeps shifting to keep up with new technology and market needs. Keeping abreast is a continuous process.
  3. Always Optimize: Keep finding ways to increase the performance, maturity, reliability, scalability, and usability of your product. Try making it domain agnostic.
  4. Have Fun: Enjoy what you are doing, and the rest will come automatically!

All the Best on your foray into the digital jungle!