Data Analytics Training in Bangalore

Data Analytics Training in Bangalore

The scope of flourishing as a Database Administrator, Business analyst, Economist or even Statistician is increasing exceedingly in Information Technology. Thus, Data Analytics Training in Bangalore will be a great choice at this point.

Why FITA?

FITA is a great place to learn with enjoyment from the knowledge accumulated by the industrial experts. Our skilled trainers will fetch you the latest updates from industry and equip you to face any technical interview.

Candidates trained in Data Analytics Courses in Bangalore are widely preferred by the organizations. As this determines the fate of a company’s success and sustainability.

Our syllabus for Data Analyst Training in Bangalore is designed with global standard for the benefit of our students.

Course Description

The Internet of Things (IoT) has built a huge platform for data sharing which in turn is very useful for business development. With the immense amount of data created and shared on a daily basis over various platforms, it is indeed necessary for us to keep the track of it. Thus, Data Analytics is boosting up its demand among various organizations.

FITA is ranked as the best institutes for Data Analytics Courses in Bangalore. This course will be beneficial for fresh graduates, business analyst, economist, and experienced professionals who are looking for domain change in the IT sector.

Data Analytics Training in Bangalore will be great choice of career now due to its revolution in the IT industry. Data Analytics is very efficient in a company’s success as this provides the information to improvise the company’s marketing strategy. It is reported to be

According to a recent survey conducted by NASSCOM only 10% of data appears under structured data and 10% under semi structured whereas remaining 80% of data’s are unstructured. The usage of traditional database tool is helpful only in the analyzation of structured and semi structured data’s.

Curriculum

Big Data Analytics introduction
 Data analytics life cycle
Data Analytic Methods Using R
Machine learning-Theory and Methods
Introduction to analytics for unstructured data-MapReduce and Hadoop
Sample analytics project

FAQs

Mention some of the tools used for data-analysis.

  • RapidMiner
  • Solver
  • Google Search Operators
  • Tableau
  • Wolfram Alpha’s
  • OpenRefine
  • Google Fusion tables
  • NodeXL
  • KNIME
  • io

 What are the basic required for becoming a data analyst?

  •  In-depth knowledge in programming languages, reporting packages and databases.
  • Ability in organizing, analyzing, and the dissemination of big data with accuracy.
  • Fundamental technical knowledge in various data models, data mining, database design and segmentation techniques.
  • Thorough statistical packages knowledge.

Mention few steps in an analytics project.

  • Data exploration
  • Modelling
  • Problem definition
  • Data preparation
  • Validation of data
  • Implementation and tracking

Mention few best practices for data cleaning.

  • Analyzing the summary statistics for each column
  • Sort data by different attributes
  • For cleaning up of large datasets, breaking them into small data will help.
  • Handling of common cleansing task , which creates a set of utility functions.
  • Keeping track of the cleaning operation date wise, in order to alter it in future.

 

List out the common problems experienced by data analyst.

  • Common misspelling
  • Varying value representations
  • Missing values
  • Duplicate entries
  • Identifying overlapping data
  • Illegal values

 

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