So, you're planning to start your career in dаta analytics, but you are confused about:
- Where to start your journey?
- Which tools to learn?
- What techniques and subjects to focus on?
- Do you need to know to code?
- And most importantly, what is the career growth in dаta analytics?
Well, if these are your concerns, no worries - We have got you covered.
And that's why we thought we should create this guide. We would love to help you get started in dаta analytics. This blog will set a framework to help you know everything about dаta analytics.
What is Dаta Analytics and Why is It in Huge Demand?
Dаta analytics refers to using quantitative and qualitative techniques and processes to inspect, cleanse, transform the dаta to discover useful information. The user extracts, categorizes, stores, and analyzes the dаta to study trends and patterns in emerging markets. It is to gain a competitive edge over rivals.
Dаta analytics can help businesses increase their revenues by optimizing marketing campaigns, improving operational efficiency and customer service efforts.
For example, let's say you own a business and sell dairy products.
Let's assume - the biggest challenge for your business is to find the right amount of stock, at the given time. You can not stock excess dairy products as they are perishable. Also, if they have become low in quality, you cannot sell them. And it will result in a direct loss.
At the same time, you cannot understock as it may result in a loss of potential customers. Here, dаta analytics can help you in predicting the strength of your customer at a given time. By using that result, you can sufficiently stock your supplies, in turn minimizing the loss.
In simple words, dаta analytics can help you find out the time of the year when your store has the least or most customers. Using this information, you can stock your supplies accordingly.
Why is Dаta Analytics Emerging in the Current Market?
Dаta analytics is used to make dаta-backed decisions and strategies to get the desired business results. Now, in India, dаta analytics has become a big career option. Businesses have realized the value of utilizing dаta analytics to increase their profits. They know that dаta is vital for their growth. Nowadays, all the major business decisions are taken after analyzing the available organization and industry dаta.
On top of it, competition is on a continuous rise. Customers are flooded with choices, and that's why it has become crucial to understand customer needs with more accuracy. And dаta analytics provides accuracy. It is based on statistical models that help in fine-tuning and analyzing the dаta.
Dаta analytics also renders the answers to existing business problems as well as give a view of future trends. This way, dаta analytics plays a huge role in preparing the company to make products for the future. And to connect with the customers of tomorrow.
Check out the Top 10 Trends that Would Drive the Scope of Dаta Analytics.
Who can become a Dаta Analyst?
Since dаta analytics is an advanced field of information technology and management, first, you need to complete your graduation with at least 60% marks (preferably in the IT and statistics stream).
Aspiring dаta analysts should have a degree in Economics, Statistics, Computer Science, Mathematics, or other subjects.
You can become a Dаta Analyst if you,
- Have time to study.
- Are committed to your goal.
Skills Required to Become a Dаta Analyst
- To become a Dаta Analyst, you must have good analytical, statistical, and problem-solving skills.
- Dаta analytics requires rigorous research and pattern evaluation, so you must also have decent coding knowledge.
- You require dаta visualization skills to perform well in the market.
- Decision making is another essential skill that you will need to pursue a career as a Dаta Analyst. With an inclination for problem-solving skills and having an analytical mind, one can easily excel in this field.
Role of a Dаta Analyst
Dаta analysts' work revolves around the dаta. A Dаta Analyst is someone who turns the raw dаta into information and information into insights. A dаta analyst extracts, collects and interprets different sorts of dаta. He/she scrutinizes the information by using dаta analysis tools.
And then, he/she pulls out meaningful results from the raw dаta. It helps the organization or clients in making important decisions.
In a nutshell, a dаta analysts’ role includes-
- Collecting dаta from primary & secondary sources & then reorganizing that dаta in a simple format.
- Using advanced computerized models to interpret and analyze the dаta.
- Identifying patterns, correlations and trends in dаtasets.
- Maintaining dаta systems and dаtabases.
- Preparing reports for managerial leadership that effectively communicate patterns, trends, and predictions using relevant dаta.
- Collaborating with engineers, programmers, and corporate leaders for process improvements, recommend system modifications, and various other activities.
What Tools Do Dаta Analysts Use?
To be able to perform dаta analysis, dаta analysts use different types of tools and software. Though there are hundreds of tools available in the market, a dаta analyst must choose wisely. The tools and software should benefit their analytical efforts. Let us talk about some tools that dаta analysts use.
1. Business Intelligence Tools
These tools are specially designed for business analytics. These tools help dаta analysts to analyze, monitor and report on crucial findings. Features such as predictive analytics and advanced SQL modes make these tools easily adjustable to every level of knowledge.
Dаtapine is a popular business intelligence tool. It is focused on delivering simple yet powerful analysis features to dаta analysts who need fast and reliable online dаta analysis solutions.
2. Statistical Analysis Tools
Computation techniques often contain a variety of statistical techniques to explore and generate insights. There exist multiple programming languages that make dаta analysts’ work easier and more effective.
R programming/R-studio is one of the best and most used dаta analytics tools. It is suitable for statistical analysis for dаta cleansing, dаta filtration, and dаta analysis. R is an invaluable analytical assistant. It covers both general and academic dаta analysis. It can also perform statistical analysis such as factor cluster analysis, regression, and conjoint, etc.
3. General-Purpose Programming Languages
Dаta analysts use different programming languages to solve a variety of dаta problems. A few programming languages used by dаta analysts include C#, Java, PHP, Ruby, Julia, and Python.
Though dаta analysts preferably use python. Its open-source solution has simple coding processes and syntax that makes it fairly easy to learn.Python can also be integrated with other languages such as PHP, C#, C/C++, Java, etc.
4. SQL CONSOLES
SQL is a programming language that analysts use to manage dаta held in relational dаtabases. It is highly popular as one of the analyst tools used in various business cases and dаta scenarios.
It is widely used in the dаta analytics field. Most of the dаta is stored in relational dаtabases, and you need to access and unlock its value.
There are different SQL based relational dаtabase management systems. It includes MySQL Workbench, PostgreSQL, MySQL, MS SQL, and Oracle.
MySQL Workbench is the most popular SQL console. Analysts use it to visually design, model, and manage dаtabases, administer MySQL environments, optimize SQL queries, and utilize a suite of tools to improve the performance of MySQL applications. It allows dаta analysts to create and view dаtabases and objects, configure servers, and much more.
5. Standalone Predictive Analytics Tools
Predictive analytics is an advanced technique. Dаta analysts who combine dаta mining, predictive modelling, machine learning, and artificial intelligence to predict future events - use it.
SAS Forecasting is one such tool that has established itself as one of the most prominent dаta analysis software. It offers a wide range of forecasting methods, including event modelling, hierarchical reconciliation, scenario planning, and what-if analysis.
6. Dаta Modelling Tools
Dаta analysts use dаta modelling tools to discover the exact nature of the information and the relationship between dаtasets.
Erwin Dаta Modeler is a very famous dаta modelling tool used to find, visualize, design, deploy and standardize high-quality enterprise dаta assets. It also helps to understand and reduce the complexities of dаta. Plus, it offers automated processes where you can automatically generate models and designs to lower errors and increase productivity.
7. Spreadsheet Applications
A spreadsheet is a traditional form of dаta analysis. People who do not have high technical skills to code themselves mostly prefer spreadsheets.
Excel is a widely used spreadsheet application. It's a versatile dаta analytics tool where you can manipulate rows and columns to do your analysis.
From arranging to manipulating, calculating, and evaluating quantitative dаta to building complex equations and pivot tables, excel has earned its place in traditional dаta analytics tools.
Conclusion
Dаta analytics also allows the business to maximize their conversion rates and cut unnecessary costs. With all these obvious advantages, it wouldn't be wrong to say that dаta analytics is making significant changes in a big economy like India.
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