Data Analytics deals with the analysis of raw data for coming to conclusions about data that an organisation has acquired or for identifying various trends and patterns. A data analytics course with placement will help you to learn and understand the anatomy of Data Analytics and how it can benefit your career so that you can get good placements. The Data Analytics techniques and methods work on certain algorithms that deal with raw data with Artificial Intelligence. The involvement of machine learning is also of prime importance.
Read along to get a brief idea of why you should take the Data Analyst certification course and how it can benefit you to boost your career.
What is Data Analytics?
Data Analytics is the process of collective transformation and organisation of raw data so that a data analyst can conclude out of it to get the desired results. It also helps the organisation to have a better decision-making process and make predictions for future operations. In today's time, a career in data science is a flourishing one and if you want to become a data scientist or data analyst, then you need to understand what are the benefits of learning Data Analytics.
A Data Analytics course with placement can help you gain the following advantages:
- Data Analytics helps to deliver business needs in a proactive and anticipating manner.
- Data analysts help to mitigate the risk factor in an organisation.
- As the data is properly understood and analysed, the results that are derived from it are always more accurate.
- All the financial, physical and intellectual assets of the company with the help of good security measures.
- Data analysts help an organisation make good investments and have productive results.
- With the help of data analysis, a company is more responsive and personalised in its services.
- Data Analytics improves and optimises the customer experience so that companions do not lose any customers.
Anatomy of Data Analytics
The factual information that you collect from multiple sources in the form of a physical or digital format is known as data. The anatomy of Data Analytics can be understood when you know about the division and classification of data. Data can be classified as follows:
The non-numeric data which is all about properties and characteristics is known as qualitative data. It is generally collected by labelling, observing, listening or watching an object. Project management uses a lot of qualitative data. Qualitative data can be generated as follows:
- By conducting interviews.
- By translation of symbols.
- By image processing.
- By making observational notes.
- By listening to multiple audios.
- By watching video recordings.
- By looking at documents and notes.
The numeric data that is statistical, conclusive, countable and measurable in nature is called qualitative data. it provides a clear picture of the aspects of numerics. Quantitative data can be in the following forms:
- Market research
- Tests and experiments
Structured data is the type of data that is present in an organised and standardised format that is easily readable and searchable. Structured data is much easier to work with and this type of data is more concise and accurate. Some examples of structured data are as follows:
- Dates and names
- Data related to product user
- ERP system data
- Bank account numbers and statements
- Identification numbers
Unstructured data is not available in an organised and standardised format. It cannot be easily searchable or readable and it is difficult to understand. This type of data is generally present in long formats. Some examples of unstructured data are as follows:
- Audio and video files
- Social media posts
- Text exchange on social media
to understand the anatomy and working model of Data Analytics and to have a career in data science, you must know what are the rules and responsibilities that a data analyst has to perform. A data analyst certification course may help you learn these. the roles and responsibilities of a data analyst are enumerated as follows:
- Ascertain organisational objectives by working closely with the data scientists and IT management teams.
- Use standardised statistical tools and techniques to analyse the result.
- Extract data from multiple sources, mainly primary and secondary ones.
- Constantly thrive for process improvement and identify different means to do it.
- Identify designs, patterns, trends and correlations in different data sets.
- Create and design RDBMS and data systems.
- prepare data reports and visual representations so that they can be presented to higher management.
- Solve data-related issues and code problems.
To become a Data Analyst, enrol yourself on a Data Analytics course with placement so that you can kickstart your career in the said field. Learn the Data Analytics course by Imarticus so that you will be able to make data-driven decisions. Proficiency in Data Analytics will help you to reach milestones in your career.