Data Analysis Basics: A Comprehensive Guide for Beginners
Are you up for a data journey? Starting out in data analysis can be challenging, especially as a beginner. That’s why we’ve created a comprehensive and easy-to-follow guide to the data analysis basics. Let’s get started right away!
Data analysis is often mixed with data analytics. Although these are related terms, they are
still specific differences. Basically, data analysis is the subcategory of data analytics, and it focuses specifically on deriving insights from data. Data analytics, in its entirety, encompasses processes beyond analysis, such as data science (utilizing data to theorize and predict) and data engineering (developing data systems).
What is Data Analysis?
Data analysis involves engaging with data to extract valuable insights, which can be used to make informed decisions.
Data Analysis Techniques for Beginners
Here are some of the most common data analytics basics techniques that will definitely help out our beginners:
These methods estimate or “model” the relationship between variables.
Factor analysis
This technique assists data analysts in uncovering the underlying variables that influence people’s behavior and choices.
Cohort analysis
In cohort analysis, customer data is divided into smaller groups or cohorts; thus, companies can observe trends and patterns over time that pertain to specific cohorts instead of treating all customer data uniformly.
Cluster analysis
Cluster analysis lets you see how data is distributed across a dataset without established predefined classes or groupings.
Data Analysis Tools
Here are the top tools necessary to learn data analysis basics :
- Microsoft Excel
- Tableau
- SAS
- RapidMiner
- Power BI
Best Practices for Data Analysis Basics
As the data accessible to companies continues to expand in volume and complexity, so does the necessity for an effective and efficient process to leverage its value. The data analysis basics process generally progresses through several iterative stages. Let’s examine each one more closely.
Identify the business question you want to address
What issue is the company aiming to resolve? What do you need to assess, and how will you evaluate it?
Gather the raw data sets required.
It will assist you in answering the identified question. Data collection may originate from internal sources, such as a company’s client relationship management (CRM) software, or external sources, like government records or social media application programming interfaces (APIs).
Prepare the data for analysis by refining it.
Cleaning the data for further analysis often involves
- removing duplicate and anomalous data
- reconciling inconsistencies
- standardizing data structure and format
- addressing white spaces and other syntax errors
Examine the data on Technically Grounds.
You can uncover trends, correlations, outliers, and variations that convey a story by applying various analysis techniques and tools. During this phase, you might utilize data mining to identify patterns within databases or data visualization software to help convert data into an easy-to-understand graphical format.
Interpret the findings of your analysis.
It determines how effectively the data addressed your original question. What recommendations can you provide based on the data? What are the limitations of your conclusions?
Data Analysis Basics: Decide Wisely For the Future
Data Analysis basics are all about making informed data decisions. If you want to extract meaning from data, you have to make worthy decisions. This emerging data analysis field is gaining fame, and skilled data analysts will continue to be in high demand. With the proper training, you can gain hands-on experience in data analysis basics and kick-start your journey as a data analyst.
