Data Analytics is the process of examining, cleaning, transforming, and modeling data with the goal of discovering useful information, drawing conclusions, and supporting decision-making.

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Data Analytics is the process of examining, cleaning, transforming, and modeling data with the goal of discovering useful information, drawing conclusions, and supporting decision-making. It involves the use of statistical techniques, mathematical models, and computational algorithms to extract insights from data. The goal of data analytics is to turn data into actionable insights and knowledge that can be used to inform business decisions, improve organizational processes, and drive growth.

Data analytics can be applied in a wide range of industries and domains, including finance, healthcare, retail, telecommunications, and government. Some common applications of data analytics include market research, customer segmentation, fraud detection, predictive maintenance, and supply chain optimization.

Data analytics can be performed using various methods, including descriptive statistics, inferential statistics, machine learning, and big data analytics. Descriptive statistics summarize and describe the characteristics of data, while inferential statistics use sample data to make inferences and predictions about a larger population. Machine learning algorithms use historical data to build models that can make predictions or identify patterns, while big data analytics refers to the processing and analysis of large and complex datasets using distributed computing technologies.

In order to be successful in data analytics, it is important to have strong analytical and critical thinking skills, as well as expertise in mathematics, statistics, and computer science. Additionally, it is important to have strong communication skills in order to effectively communicate insights and findings to stakeholders.

  • More than 55% of IT industries have been shifted to the cloud space and the numbers are expected to increase by over 25% in the future. And it has been predicted by Forbes that more than 80% of Enterprise Workloads will efficiently be handled through cloud technologies.
    • Unlike different disciplines, the salary of a Data Analytics professional is usually 30 percent higher.

      At the beginner level, you can earn up to $113K per annum.

      Even with less than one year of experience, you will make around Rs.4, 80,000 in a year.

  • Data Analytics certified are high in demand and gaining significant traction in the US and Canada. People with years of experience can earn maximum of Rs. 1,800,000 per annum.

  • No matter whether you are a fresher or an experienced professional, our Data Analytics course will help you gain the relevant skills you required. If you are looking to start a career in the field of cloud, we will help you gain all essential skills and let you clear the global certification examination, too.
    • Establish yourself as a certified Data Analytics professional and get hired by leading IT industries.

      Clear the interview and gain all essential technical and communication skills.

      Get a more than 30 percent hike in salary as a certified professional.

  • On the course completion, attempt the Data Analytics exam and clear it in the first attempt as we assure 100% clearance rate for our students.

  • There’s no denying that Data Analytics now become the future in today’s tech-dominating landscape. As most of the industries are aggressively adopting the best Data Analytics solutions, the demand for skilled Data Analytics professionals has been increased worldwide.
  • The reasons behind the popularity of Data Analytics are as follows:
    • A multitude of career benefits as an Data Analytics professional

      In-demand Data Analytics skills

      Placement Assistance

      Beyond expected salaries

      Best-in-class course content curated by leading industry practitioners.

The job roles and responsibilities of a data analyst can vary depending on the industry, organization, and specific job function. In general, however, data analysts are responsible for the following:

  • Collecting, Cleaning, and Preparing Data: Data analysts must collect and organize data from various sources, clean and preprocess the data to remove errors and inconsistencies, and prepare the data for analysis.
  • Analyzing Data: Data analysts use statistical methods and machine learning algorithms to analyze data, identify patterns and trends, and generate insights that can inform business decisions.
  • Creating Reports and Dashboards: Data analysts create reports, dashboards, and visualizations that summarize and communicate key findings and insights to business stakeholders.
  • Communicating Findings: Data analysts must be able to effectively communicate their findings to non-technical stakeholders, and explain the implications of their analyses in a clear and concise manner.
  • Identifying Business Opportunities: Data analysts may also be responsible for identifying business opportunities, such as potential new revenue streams, cost savings, or process improvements based on data analysis.
  • Monitoring Performance: Data analysts may also be responsible for monitoring and tracking key performance metrics, and identifying areas where performance can be improved.
  • Collaborating with Other Teams: Data analysts often collaborate with other teams, such as data engineers, data scientists, and business stakeholders, to ensure that the organization’s data needs are met.

Overall, the primary responsibility of a data analyst is to extract insights from data and use those insights to inform business decisions. This requires a combination of technical skills, such as data analysis and visualization, as well as soft skills, such as communication and collaboration.

  • Top industry verticals:
    • Travel Industry, IT Sector, Healthcare and Medical Sector, Media & Entertainment, Banking & Finance, Transportation, Non-Profit Industries, eCommerce, Insurance Sector, etc.

  • Top hiring companies:
    • IBM, NETFLIX, FEDEX, Infosys, American Express, etc.

  • Benefits of getting trained with us:
    • Find yourself a more competent, confident, and knowledgeable resource.

      Crack any interview with leading industries without any difficulty.

      Start working in your dream company like a PRO.

      See a drastic change in your communication skills.

  • You will get a completion certification to validate your skills after the completion of Data Analytics certification training. Also, you are likely to get recognized among top corporate giants. When it comes to enhancing your overall career, we endeavor to give the maximum support.
    • Our training certificate is globally accepted

      Helps the learner to climb the professional ladder

      It showcases credibility

      Increases your earning potential

      Makes you stand tall above the rest

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Plenary for Data Analytics Program

Track Week Days Course Duration Fast Track
Course Duration 40-45 Days 7 Weekends 8 Days
Hours 2 Hrs. Per Day 3 Hrs. Per Day 6+ Hrs. Per Day
Training Mode Online Online Online
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There are no specific eligibility criteria to enroll in our Data Analytics course. Anyone interested in starting a career in Data Analytics can register for this Data Analytics training program and become job-ready.

Yes, our dedicated crew of professional regularly updated the content of our course; ensuring students must get the latest knowledge.

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There are several benefits to taking a data science course:

  • In-demand skill: Data Analytics is a high-growth field that is in high demand across a variety of industries, and taking a data science course can help you gain the skills necessary to pursue a career in this field.
  • Better job prospects: With the rise in data-driven decision making, businesses are increasingly looking for professionals who can analyze data and provide insights that can help drive decision making, which means a data science course can help you enhance your job prospects.
  • Enhanced analytical skills: Data Analytics courses can help you develop analytical and critical thinking skills, enabling you to better understand complex data sets and identify patterns, trends, and relationships.
  • Multidisciplinary approach: Data Analytics courses provide a multidisciplinary approach to analyzing data, which combines expertise in statistics, computer science, and domain-specific knowledge.
  • Practical experience: Many data science courses provide hands-on training and project work, giving you practical experience in applying data science techniques to real-world problems.
  • Competitive edge: Taking a data science course can give you a competitive edge in the job market, as it demonstrates your commitment to developing skills in a high-demand field.
  • Lifelong learning: Data Analytics is an ever-evolving field, and taking a course can provide you with a foundation for lifelong learning as you keep up with new developments and technologies.

Overall, taking a data science course can provide you with a competitive edge, develop your skills, and open up new career opportunities in a high-demand field.

There are no prerequisites associated with our Data Analytics courses. It can be taken up by beginners as well as experienced professionals who want to gain in-demand Data Analytics skills.

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