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Defour Analytics has strong alliances with employers and industry partners that help participants with payback opportunities for their learned skills and competencies. Our association helps in exploring the possibilities for placements, industry projects and internships for better career growth. Defour is also in-sync with the changing trends of the young generation and offers a blend of empowered individuals who apply a modern approach to solving problems while adhering to traditional values. These engagements will also benefit aspirants with internship and job opportunities.

Defour?s Placement Vertical works with potential employers to understand their needs, analyze them and create suitable opportunities for participants. Apart from seeking opportunities Defour?s The Placement Cell also organizes workshops on a range of topics covering professional development, communication skills, interview process/ skills, and career guidance to enhance employability. 

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Hire Our Highly trained and skilled data science aspirants. Employee recruitment agencies/ industries can reach us by sending their requirement to Defour? Placement vertical. Our experts will share suitable profiles.

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Data Science is most fast-evolving field. Every other day a new technology is evolving to solve most complicated business analytics problems. Defour understands this and always keen to upgrade and give exposure to participants with the latest Technology in Data Science.

  1. Deep Learning:- Deep Learning is a sub-field of a broader concept of Artificial Intelligence which is concerned with algorithms influenced by the structure and function of the Human brain called artificial neural networks. It is a method that teaches computers to learn from human activities
  2. Artificial Intelligence:- Artificial intelligence is a branch of computer science. Its objective is to create an intelligent computer/robot that will perform human activities like speech recognition, learning, planning, problem-solving
  3. Apache Spark:- It is an open source general-purpose cluster computing framework for running large –scale data analytics applications.
  4. Apache Storm:- Apache Storm is a free and open source distributed real-time computation system, which makes it easy to process unbounded streams of data.
  5. CASSANDRA:- Cassandra is also designed to handle large amounts of data across many servers, providing high availability with no single point of failure.
  6. Neural Networks:- It is a technique/ algorithm which is used in Machine learning and Deep Learning.
  7. SQL, No-SQL:- SQL stands for Structured Query Language used to communicate with Database. No-SQL stands for not only SQL, but it is also non-adherence to Relational Database Concepts.
  8. MongoDB:- MongoDB is an open source DBMS that uses a document-oriented data model and a non-structured query language.
  9. Big Data – Hadoop:- Hadoop is an open source software framework. It is used in storing huge data and big data applications running in a clustered system.
  10. Pentaho BI:- It is a modern Business Intelligence tool which performs various tasks involved in data analytics like Data Integration, reporting, data mining, and dashboard.
  11. QlikView:- QlikView is fastest growing Data Visualization and Business Intelligence Tool, which helps many organizations to visualize data and create a story from data.
  12. Blockchain:- Blockchain is a new invention in Data Science world, in which a lot of information, past records is stored in blocks in a distributed manner.


Data Science can be termed as obtaining insights and meaningful information from various structured and unstructured data generated from various sources which help to solve business problems. This field employs mathematics, statistics, and computer science disciplines, and incorporates techniques like machine learning, cluster analysis, data mining, and visualization. On the basis of data analysis, you can know how to predict/forecast, improve efficiency, process optimization, etc. So all the actions/decisions will be data-driven. 









Industry Demand:-

Data Science is a field which is constantly evolving and constantly making way for new technologies to be picked up. Many companies and professionals are mastered to stay ahead in the competition. In this data-driven era, all type of small and medium-sized businesses are investing their bucks on hiring different Data Analytics related talents.

A recent study titled, State of Analytics At Domestic Firms In India 2018 by Analytics India Magazine and INSOFE suggests that Indian analytics, Data Science and big data industry is estimated to be $2.71 billion in revenues and growing at a healthy rate of 33.5 percent CAGR. According to the study, telecom, financial services, e-commerce, and private sector banks have almost 100 percent adoptions rates, whereas the infrastructure sector has no adoption of analytics.


Types of Jobs:-

As this field is further broken down in terms of skill requirements, there are many interdependent roles that emerge and the definitions of these roles are also dynamically evolving.

Job portals globally have seen a significant hike in Big Data related postings in the past few years.

Data Science Professionals have a wide range of job titles and fields available in the market. Some of them listed below:-

  1. Data Scientist:- Data Scientist is the most demanding job title among all companies like Google, Microsoft, Facebook. The Data Scientist is a person who has deep knowledge of data science and masters a whole range of skills and talents going from being able to handle the raw data, analyze that data with the help of statistical techniques to sharing the insights with the organization in a compelling way.
  2. Data Analyst:- Data Analyst should have the knowledge of languages like R, Python, SQL, Excel, Tableau and more. The job might consist of tasks like pulling data out of SQL databases, becoming an Excel or Tableau master, and producing basic data visualizations and reporting dashboards.
  3. Business Analyst:- It is the less technical oriented job and business analyst do their jobs with a deep knowledge of business process efficiently and effectively. They often act as the intermediary between the business guys and the techies.
  4. Data Architect:- The person in this role creates the blueprints for data management systems to centralize, integrate, maintain, and protect the data sources. Data Analyst and Database Designer makes the role of a Data Architect. They integrate data from different unrelated data sources to help find relevant information.
  5. Data Engineer:- The ones going for data engineer job profile often have a background in software engineering and loves to handle databases and large-scale processing systems. The data engineers can easily master technologies and therefore, is familiar with a diverse set of languages that span both statistical programming languages and languages oriented more towards web development.

The other job profiles are: Data and analytics manager, Database administrator, functional consultant, etc.

Fast Track Course in One Month

Learn Python for Data Science

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