What is Data Analytics, and Why Is It So Relevant Today?

Before we dive too deep into our data analytics guide, it is important to define “data analytics.” Generally speaking, big data refers to massive data sets that are too complicated to be processed and analyzed via traditional applications. Instead, analysts must use predictive tools and machine learning technologies to extract actionable insights from these data sets.

Data analytics is used for many purposes, such as digital marketing and project management. Businesses can also leverage data analytics to predict the likely outcomes of major events impacting their bottom line. For instance, data analytics can help a corporation project how a new product will perform upon release.

Importance of Data Analytics for Large Corporations

The growth of the big data analytics market projected by Statista reveals how valuable this approach is to large corporations. Stakeholders and thought leaders understand that innovative analysis technologies can give them a competitive edge within their respective industries.

While big data analytics can produce many benefits for an organization, we have identified a few of the most notable below:

• Optimized spending and cost reduction: Data analytics tools help corporations optimize spending and reduce costs. These technologies allow businesses to efficiently store, process, and analyze massive amounts of data, revealing valuable insights into ways a company can refine its current business practices.
• Enhance efficiency: Data analytics tools can improve the efficiency of day-to-day operations by assessing customer feedback and interpreting this data to create more personalized services, products, and advertising content.
• Develop competitive pricing strategies: The most effective way to develop competitive pricing strategies is to use data analytics to track competitor actions and assess customer demands to implement sound pricing.
• Improve sales: Optimizing business processes with data analytics can improve sales and profitability, fostering consumer loyalty.
• Fuel innovation: Data analytics is the most effective mechanism for fueling innovation. It allows corporations to identify pain points and create products that address those needs.
• Manage brand reputation: Big data analytics tools provide insights into user experience, enabling companies to adjust their online strategy to address customer grievances and enhance brand reputation. Corporations can identify pain points by analyzing customer data and creating products to fill those needs. They can also improve upon existing products or services by shifting consumer desires. In light of this fact, it is vital that corporations provide users with an enjoyable online experience.

Types of Data Analysis

In the next part of our data analytics guide, we’ll focus on the various methods of exploring these massive amounts of information. There are four broad types of data analysis:

• Descriptive Analysis: Used to describe an event by summarizing past data, typically presented with visual charts like bar graphs and pie charts.
• Predictive Analysis: Uses statistical modeling to answer the question, “What will likely happen next?” and is primarily used by large corporations for sales forecasting and risk assessment.
• Diagnostic Analysis: Seeks to reveal why something happened by identifying correlations between events and isolating causal factors.
• Prescriptive Analysis: The newest field of data analytics relies heavily on machine learning and AI to forecast outcomes and prescribe viable means of altering them.

What Are the 5 Steps of the Data Analysis Process?

The data analysis process for all four types of data analysis can be divided into 5 general steps. These stages are as follows:

1. Define the data you need: Determine which questions you want to answer to identify the type of data analysis required and clearly define research objectives.
2. Data Collection: Gather relevant information, which can be straightforward or complex depending on data availability.
3. Data Processing: Also known as “data cleaning,” this step involves transforming raw information into usable intelligence by addressing missing values and inconsistencies.
4. Data Analysis: Researchers look for relationships, hidden patterns, correlations, and other valuable insights during this phase.
5. Data Interpretation: Analysts draw meaningful conclusions based on their findings and present them to stakeholders compellingly.

Skills Required to Become a Data Analyst

Data analysts are incredibly organized and talented individuals with diverse skills. These include:

• Critical Thinking Ability: Allows analysts to ask the right questions and uncover connections that may not be immediately clear.
• Communication and Interpersonal Skills: Analysts must effectively convey their findings using various methods, including detailed emails, visual charts, and verbal summaries.
• Technical Skills: Data analysts must possess comprehensive technical skills to utilize IT resources like SQL, Python, and machine learning tools like Asana and Tableau.

How Do Beginners Learn Data Analytics?

As the digital marketplace becomes more competitive, the demand for data analysts will continue to surge. This exciting career field offers competitive salaries and opportunities for gainful employment with major organizations. Here’s how you can get started:

• Pursue Higher Education: While not mandatory, many employers prefer analysts with degrees in fields like mathematics, computer science, or statistics.
• Learn Core Data Analytics Skills: This includes becoming familiar with SQL and either Python or R programming languages.
• Consider Getting Certified: Specialized analytics certifications are a great way to demonstrate expertise. Pathstream offers the Tableau Data Analytics Certificate, which can be completed online.
• Apply for Jobs: New analysts can apply for data analyst jobs or check if their organization partners with Pathstream to access our programs at no cost.

Recapping Our Data Analytics Guide

Has our data analytics guide inspired you to pursue a career in this dynamic field? Are you ready to start building high-demand digital skills? If you’re looking for a flexible and convenient way to learn, Pathstream can help.

Many companies partner with us to offer access to our data analytics programs as part of their education benefits. Find out if your employer is one of our many partners and if you can take our programs for free. Learn more today.