Free Data Analyst Training With Free Virtual Internships
In a world where organizations are diving into the tech space with enthusiasm, acquiring tech skills is the current trend. Different companies are seeking trained data analysts to make informed decisions to improve company standards and proffer effective marketing strategies. Becoming a Data analyst is not a hard nut to crack these days. You can become a data analyst in 90 days, with a free data analyst training course, land a gig and increase your paycheck.
If you want to upskill in Data Analysis, stay glued to this post because I am going to share information about where you can learn for free with free virtual Internships. This implies that you will be trained and also receive experience to kick start your Data Analyst career.
List of data analyst tutorials:
- Excel.
- Basic statistics.
- SQL.
- Python.
Excel
Microsoft Excel is the commonest software tool in data analysis. Starting with a foundational course in Excel prepares you to organize large amounts of data and perform complex analyses. This tool helps to import data from various sources and organize the data for analysis. It’s an excellent mathematical ability that helps you to perform mathematical calculations seamlessly. The strong visual aspect of Excel keeps your data understandable. Also, charting and graphic customizable tools helps you to create graphs to suit your needs.
Importantly, Excel helps you to collaborate with other users on a single project. This feature is useful for large teams working on a particular data analysis project.
Start your Excel journey with this tutorial
Basic statistics
For the past three-and-a-half centuries, statistics has played an important role in the field of data analytics. Statistics is a mathematical branch that involves the manipulation of data. This data can be quantitative or qualitative. It provides users with a means for collecting, reviewing, and analyzing data, as well as a way to draw conclusions from this data to make better business decisions.
Furthermore, statistics helps to detect the structure of data to identify anomalies and trends. It provides insights into business operations and aids data processing amongst other numerous features.
Start your statistics journey with this comprehensive guide
SQL
SQL (Structured Query Language) is a Database Management language. It has been around since the 1970s and is still the most popular way to access data in Databases today. SQL provides a number of operations that enable users to read, manipulate, and change data. The SQL software is widely used by engineers in software development, but it is also widely used by Data Analysts. Additionally, it helps to conduct aggregations similar to the Excel pivot table like: sums, counts, minimums and maximums.
The seamless storage of data in a particular database type, and provision of flexibility to access the data or update it easily, can be achieved with SQL. Data analysts, before performing any analysis, need a dataset. They create datasets, and perform actions like updating the data or deleting it, only if they know SQL. Data Analysts need to understand how to handle structured data.
Click here to watch full SQL for beginners
Python
Python has become a popular programming language for data analysis and data science due to its simplicity, versatility, and a wide range of libraries and frameworks specifically designed for data manipulation, exploration, and visualization. Several libraries for creating visualizations such as Matplotlib, Seaborn, Plotly, and Bokeh is imbedded in python. These libraries make it easy to create a variety of charts, plots, and graphs that can help data scientists quickly identify patterns and trends in data.
Cleaning and preprocessing data is an important step in data analysis. Python’s Pandas library provides tools for handling missing data, filtering, and cleaning data, making it easier to prepare data for analysis. Many businesses have chosen Python as a popular choice, as they need to process and analyze large amounts of data.
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Benefits of being a data analyst
Here are some interesting benefits of being a data analyst.
1. High compensation
Data analysts are well paid due to the job demand. Befitting salaries are paid to both entry level data analysts and senior level data analysts.
Junior and senior data analysts are paid salaries that range from $57,000 to $74,000 in a year. This includes bonuses, overtime, and tips. The attractive financial compensation in salaries and perks makes data analysis a good career to consider. Compared to other jobs, a junior-level position in data analysis earns higher than professionals in different fields.
2. High demand
Data analyst professionals are some of the most sought-after professionals in the world. This is because of the high demand for data analysis and the limited supply of experts in this field.
3. Contribute to Decision Making Process
The role of data analysts make them vital decision-makers. Data analysts interpret data and show trends and statistics that will determine the direction of a company.
They process huge amounts of data to produce meaningful information that businesses use to make investment decisions. Business owners use this information to target customers, assess risks and allocate capital.
4. Growth opportunities
Senior data analysts started out as entry level data analysts. There’s always room for growth in the data analysis.
5. Job security
There is a high demand for data analysts as data creation and collection increase. A report according to IBM predicts that jobs for data analysts will continue to surge. The report forecast 364,000 to 2.72 million jobs in data analysis.
Free virtual Internships for data analysts
Jump on this Free data analyst training opportunity today, to switch your career into the tech space.