Introduction to Business Analytics (Updated Edition)
Cody Baldwin・2 minutes read
Business analytics is a hot topic, with resources available at codybaldwin.com, involving turning data into valuable insights through cleaning and analysis. Different terms like business intelligence and data science are related to analytics, with key types including descriptive, predictive, and prescriptive analytics, and a life cycle similar to the scientific method.
Insights
- Business analytics involves transforming data into valuable business insights by cleaning and analyzing data to extract meaningful information, crucial for decision-making in various industries like finance and technology.
- The field of analytics encompasses various terms such as business intelligence, decision science, and data science, each aiming to leverage data for useful insights, with three key types of analytics being descriptive, predictive, and prescriptive, guiding businesses through the analytics life cycle from understanding the data to deploying models using tools like Excel, Tableau, Python, and SQL.
Get key ideas from YouTube videos. It’s free
Recent questions
What is business analytics?
Business analytics involves turning data into valuable business insights through data cleaning and analysis to filter out noise. It includes customer analysis for credit card companies, employee data analysis for tech companies, and loan data analysis for banks.
What are the key types of analytics?
The key types of analytics are descriptive (past data analysis), predictive (future predictions), and prescriptive (future actions based on predictions). These types aim to provide valuable insights for businesses to make informed decisions.
How does the analytics life cycle work?
The analytics life cycle, similar to the scientific method, includes stages such as business understanding, data understanding, data preparation, modeling, and model evaluation and deployment. This structured approach helps businesses derive meaningful insights from data.
What are some popular analytics tools?
Popular analytics tools include Microsoft Excel, Tableau Desktop, Python, and SQL. These tools are used for data visualization, analysis, and modeling to extract valuable insights from data for businesses. Other options like Microsoft Power BI and R are also commonly used in the industry.
What are the related terms to business analytics?
Related terms to business analytics include business intelligence, decision science, and data science. These terms are all interconnected and aim to turn data into useful insights for businesses to improve decision-making processes.
Related videos
DWIVEDI GUIDANCE
Business Analytics, Descriptive analytics, prescriptive, Business Statistics and Analytics aktu,
Simplilearn
Data Analytics For Beginners | Introduction To Data Analytics | Data Analytics Using R | Simplilearn
edureka!
Business Analyst Full Course [2024] | Business Analyst Tutorial For Beginners | Edureka
Cognitive Class
Big Data 101 Module 3 Video 1 Updated
codebasics
What is Data Science? | Free Data Science Course | Data Science for Beginners | codebasics
Summary
00:00
"Business Analytics: Turning Data into Insights"
- Business analytics is a popular topic currently, with a cheat sheet available for download at codybaldwin.com.
- Analytics involves turning data into valuable business insights, often requiring data cleaning and analysis to filter out noise.
- Examples of business analytics include customer analysis for credit card companies, employee data analysis for tech companies, and loan data analysis for banks.
- Different terms like business intelligence, decision science, and data science are related to analytics, all aiming to turn data into useful insights.
- Three key types of analytics are descriptive (past data analysis), predictive (future predictions), and prescriptive (future actions based on predictions).
- The analytics life cycle, akin to the scientific method, includes business understanding, data understanding, data preparation, modeling, and model evaluation and deployment.
- Popular analytics tools include Microsoft Excel, Tableau Desktop, Python, and SQL, with additional options like Microsoft Power BI and R for visualization and modeling.
