What is Data Analytics

Data analytics is the process of inspecting, cleaning, transforming, and modeling data in order to discover useful information, draw conclusions, and support decision-making. It involves applying statistical techniques, mathematical algorithms, and visualization methods to identify patterns, trends, correlations, and insights within data. Data analysis can be performed on various types of data, such as numerical, textual, or categorical data, and it is commonly used in fields such as business, finance, marketing, healthcare, and social sciences. The person who does all this is called a data analyst. 

Who is a data analyst

A data analyst is a professional who collects, organizes, and analyzes large sets of data to identify patterns, trends, and insights. They use various techniques and tools to extract valuable information from data, which is then used by organizations or businesses to make data-driven decisions and improve their operations. Data analysts often have skills in data manipulation, statistical analysis, data visualization, and programming languages such as SQL or Python. 

Types of Data Analysis

There are different types of data analysis, which are:

• Descriptive: this explains a past event
• Diagnostic: it looks at the condition responsible for an event
• Predictive: predictive is used to make a forecast about a future event
• Prescriptive: this examines what has happened, why, and what might be done to prevent it or what not to do. 

Google Data Analytics Professional Certificate

The Google Data Analytics Professional Certificate is a program offered by Google in partnership with Coursera. It is designed to teach individuals the essential skills and tools needed to work with data and analyze it effectively.

The certificate program consists of six courses, covering topics such as data analysis, data visualization, data cleaning, and working with spreadsheets, SQL, and Tableau. It is a hands-on program, with participants getting the opportunity to work on real-world projects using real data. 

By completing the certificate program, individuals will gain the skills necessary to start a career in data analytics. The program is suitable for beginners, as no prior experience is required. It can also benefit professionals already working with data who want to enhance their skills or transition to a career in data analytics.

Upon completion of the program, participants receive a certificate from Google, which can be showcased on their resume and LinkedIn profile. It can help individuals stand out to potential employers and demonstrate their proficiency in data analytics. 

Data Analytics Tools for Handling Medium to Large Data

These days there are a lot of data analytical tools available in the market. They are used for different purposes depending on the profession of the user. The most commonly used tools include;

• Tableau: Tableau is a powerful data visualization and analytics tool that helps businesses analyze and present data in a visually appealing way.
• Power BI: this is a business analytics service by Microsoft that provides interactive visualizations and business intelligence capabilities.
• SAS: SAS is a software suite that offers advanced analytics, multivariate analyses, business intelligence, data management, and predictive analytics.
• Python: Python is a programming language that offers various libraries and tools for data analysis, such as NumPy, Pandas, and Scikit-learn.
• R: R is a programming language and environment for statistical computing and graphics, widely used for data analysis and visualization.
• Apache Spark: Apache Spark is an open-source distributed computing system that provides a fast and general-purpose framework for processing big data.
• QlikView: QlikView is a business discovery platform that enables self-service data visualization and analysis, allowing users to explore data and make informed decisions.
• Excel: Microsoft Excel is the most used spreadsheet program that also offers basic data analysis capabilities, including formulas, pivot tables, and charts. 

How Does Data Analytics Work?

Analytics works by collecting, analyzing, and interpreting data to derive meaningful insights and patterns. Here is a basic process of how analytics works:

Data collection

The first step is to collect relevant data from various sources such as websites, applications, sensors, social media, customer databases, etc. It may involve structured data (like spreadsheets) or unstructured data (like customer reviews).

Data cleaning and preprocessing

This process involves data cleaning, removing duplicates, dealing with missing values, and standardizing data formats.

Data analysis

In this step, various statistical techniques and algorithms are applied to the preprocessed data.

Data visualization

The analyzed data is typically visualized through charts, graphs, and dashboards to make it easier for users to understand and interpret. Visual representations enhance data comprehension and facilitate decision-making.

Interpretation and insights

Analysts interpret the results of the analysis to extract meaningful insights, correlations, and trends. These insights can be used to answer specific questions, make informed decisions, optimize processes, or identify opportunities for improvement.

Decision-making and action

Based on the insights gained through analytics, businesses can make data-driven decisions, devise strategies, and take appropriate actions. Analytics helps organizations identify areas of improvement, allocate resources efficiently, and achieve their goals. 

How to get started

You can follow the below steps to get started on your data analytics journey!

• Learn how to use an analytical tool
• Practice regularly and develop a portfolio of your work
• Join online community
• Practice with real-life projects
• Get an entry-level data analyst job 
• Pursue advanced studies certificate 

Difference between data and business analytics

Data analysis focuses basically on data mining or collection of data interpreting the data and deriving interpretation from the collected that without considering other external effects that might impact the situation. Business analysis however is a wholistic approach to how the analysed data can be used to make an impactful decision on business, it puts conditions like market trends, government policy, and every other factor that might affect the business into consideration.

Moreover, data analytics is an information technology job whereas business analytics is primarily not an information technology job unless integrated into the information technology department in a situation where the data analytics department is not specialized. 

With an Advanced Studies in Data Analytics

With a master's degree in data analytics, you can become a:

• Data Engineer
• Data Scientist
• Data visualizer
• Data Governance Analyst
• Risk analyst

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