how to start learning Data Analytics

2. How to start learning Data Analytics https://iimskills.com/how-to-start-learning-data- analytics/

3. Overview How to Start Learning Data Analytics We live in a world where the internet is no longer a luxury but a necessity and data is no more mere numbers but a golden pathway to stay one step ahead in this competitive world. The Internet has taken the world by storm and when you can learn to build a car from scratch, why not work on How to Start Learning Data Analytics on your own, and figure out a way? In this article, we focus on why you should think of stepping into this field, how could you become an Analyst and the benefits of Data Analytics.

4. Introduction to Data Analytics- Understanding the Fundamentals How to Start Learning Data Analytics especially if you are from a non- technical background? If you have an analytical bend of mind, are interested in learning new technology, and mathematics and statistics are subjects that interest you, then it is easy for you to start learning Data Analytics on your own. The only prerequisite is that you are ready to learn new things and upgrade your knowledge constantly and are ready to evolve. To start your journey on “How to Start Learning Data Analytics”, first let’s focus on what are the fundamental topics falling under the purview of Data Analytics.

5. Data Collection: The methods for Data Collection can be classified under two categories, Primary and Secondary. Primary Data Collection is when the data is collected directly from the respondent which is known as primary data collection. The researcher has the advantage of altering the collection method that suits their purpose. The methods involved in this type of collection are surveys and questionnaires, interviews, study groups, and focus groups. Secondary Data Collection is when the information is collected from pre-existing data, then it is known as Secondary Data Collection Method. The sources to apply this method are published sources like newspapers, medical journals, surveys, statistic reports, government records, and data published for the public by individuals like expert opinions, and social organizations, this is a secondary method of data collection and past research studies.

6. Data Preprocessing and Cleaning: The data when collected is in raw form. It is then cleaned, modified, and consolidated before it is subjected to analysis. This process is known as Preprocessing. The methods for processing are Data Cleaning in which errors like outliers, duplicate data, and missing values are identified, and removed with the help of methods like Binning method, regression, and clustering. Data Transformation is the second step and it is the process of categorizing the cleaned data into set formats for ease in Analyzing. The methods employed for this are Dicreditization, Concept Hierarchy generation, and Attribute Selection. Normalization, Standardization,

7. Conclusion: In conclusion, Data Analytics is a dynamic, and constantly evolving field in which new technologies keep getting introduced frequently. If you are looking for a career that is dynamic, growing and holds an important place in the company, then Data Analytics is the right choice. As it is clear in this article, your journey on “How to Start Learning Data Analytics” by yourself is not that complicated. An aspiring data analyst can start learning right from home.

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