How to Be Data Analysis Generalist - Job Description, Skills, and Interview Questions

Jan 3, 2020 / 5 Minutes Read / By Albert

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The role of a Data Analysis Generalist is to bridge the gap between data scientists and business leaders. They are responsible for gathering, analyzing, and interpreting large amounts of data to determine trends and patterns, and then providing meaningful insights to help the business make informed decisions. By doing so, Data Analysis Generalists are able to help businesses better understand their customers, optimize their operations, increase profitability, and gain a competitive edge. With the increased reliance on data-driven decision making, the demand for Data Analysis Generalists is expected to increase significantly in the coming years, and those with the skillset will have a competitive advantage in the job market.

Steps How to Become

Earn a Bachelor's Degree. The first step to becoming a data analysis generalist is to earn a bachelor's degree in a related field, such as computer science, mathematics, statistics, economics, or business analytics.
Gain Experience. With a degree in hand, the next step is to gain experience in data analysis. This could be done through internships or working as an entry-level data analyst.
Develop Essential Skills. To become a data analysis generalist, you will need to develop specific skills like data visualization, data wrangling, and machine learning. Take classes or tutorials to learn these skills.
Earn a Masters Degree. A master's degree in data science, analytics, or a related field will help you stand out from the competition and open up more opportunities.
Become Certified. Earning certifications in data analysis can also give you an edge when applying for jobs. Certifications show employers that you have the necessary knowledge and skills for the job.
Network. Networking is important for any career path, and data analysis is no different. Attending conferences, joining professional organizations, and connecting with other data analysis professionals in your area can help you stay up to date on industry trends and find job opportunities.

Data Analysis Generalists are highly skilled and competent professionals responsible for analyzing large data sets and deriving meaningful insights from them. They use a variety of techniques such as predictive analytics, data mining, and machine learning to identify patterns and correlations from the data. By leveraging these skills, they are able to make informed decisions that can lead to improved operational efficiency, increased profits, and better customer service. As a result, businesses have come to rely heavily on the work of Data Analysis Generalists to keep their operations running smoothly.

You may want to check Business Intelligence Generalist, Facility Management Generalist, and Administrative Generalist for alternative.

Job Description

Data Analysis Manager: Responsible for managing and overseeing data analysis projects, developing and implementing data analysis strategies, and providing guidance to data analysts.
Data Analyst: Responsible for collecting, organizing, analyzing, interpreting and visualizing data to provide actionable insights and support decision-making.
Business Intelligence Developer: Responsible for designing, building and maintaining business intelligence (BI) solutions to support the organizations data analysis needs.
Data Scientist: Responsible for analyzing large amounts of structured and unstructured data to identify patterns, trends and correlations to help the organization gain valuable insights from their data.
Data Visualization Specialist: Responsible for creating visualizations of data to help the organization better understand their data.
Database Administrator: Responsible for managing, maintaining and monitoring databases used for data analysis purposes.

Skills and Competencies to Have

Data Management: Ability to collect, organize, store, clean and manipulate large sets of data.
Statistical Analysis: Knowledge of various statistical analysis techniques, including regression, correlation, multivariate analysis, and hypothesis testing.
Data Visualization: Ability to effectively communicate complex data sets through graphs, charts, infographics, and other visual methods.
Programming: Knowledge of relevant programming languages such as Python, R, and SQL.
Machine Learning: Understanding of machine learning algorithms and techniques.
Business Intelligence: Ability to translate data into actionable insights and solutions for business problems.
Database Design: Knowledge of database design principles and best practices for designing efficient and secure databases.
Project Management: Ability to manage multiple projects at once and meet deadlines.
Problem-solving: Ability to think logically and troubleshoot data-related problems.
Communication: Ability to effectively communicate data insights to stakeholders in a clear and concise manner.

Data analysis generalists are highly skilled professionals who possess a wide range of knowledge and experience in data analysis. They are responsible for interpreting, analyzing, and presenting data in a meaningful way to support decision making. This requires a deep understanding of data management, statistical analysis, and visualization techniques.

The role of a data analysis generalist is essential to the success of any organization that relies on data to make informed decisions. Their expertise helps to identify trends, gain insights, and optimize processes. As a result, organizations can make informed decisions that are based on accurate data, leading to improved efficiency and effectiveness.

data analysis generalists can provide invaluable insights into the performance of an organization and its strategies. By having a comprehensive understanding of the data, they can help to reduce risk and ensure that the organization is making the best decisions possible.

Recruiting Generalist, Project Management Generalist, and Tax Accounting Generalist are related jobs you may like.

Frequent Interview Questions

What experience do you have with data analysis?
How do you stay up to date with new data analysis techniques and trends?
What methods do you use to analyze data?
How do you interpret data to draw meaningful conclusions?
How do you identify and address errors in data?
Describe a data analysis project you have worked on and what the results were.
What challenges have you faced when analyzing data?
How do you ensure accuracy when analyzing data?
How do you collaborate with other teams in order to analyze data?
What tools and software do you use for data analysis?

Common Tools in Industry

Microsoft Excel. A spreadsheet program used for data analysis and visualization. (Eg: creating pivot tables, plotting graphs, and performing statistical analysis)
Tableau. A data visualization software used to create interactive graphs and dashboards. (Eg: creating bar charts, scatter plots, and heat maps)
SQL. A database language used to query, manipulate, and analyze data. (Eg: creating queries to join tables, filtering data, and generating reports)
R Programming Language. A programming language used to create statistical models and perform data analysis. (Eg: running linear regressions, creating predictive models, and performing time series analysis)
Python. A programming language used to create scripts and perform data analysis. (Eg: writing functions, automating tasks, and creating data visualizations)
SAS. A software suite used to analyze data and generate reports. (Eg: running statistical tests, creating predictive models, and generating data summaries)
SPSS. A statistical software used for quantitative data analysis. (Eg: running statistical tests, creating regression models, and producing descriptive statistics)

Professional Organizations to Know

American Statistical Association (ASA)
International Association for Statistical Computing (IASC)
Data Science Association (DSA)
Institute for Operations Research and the Management Sciences (INFORMS)
Association for Computing Machinery (ACM)
International Society for Bayesian Analysis (ISBA)
Predictive Analytics World (PAW)
The Guild of Data Scientists
R-Core Group
International Machine Learning Society (IMLS)

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Common Important Terms

Data Mining. The process of discovering patterns in large datasets using algorithms and statistical models.
Machine Learning. A type of artificial intelligence that uses algorithms to learn from data and make predictions.
Predictive Analytics. The use of data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data.
Natural Language Processing (NLP). A form of artificial intelligence that allows computers to understand and interpret human language.
Data Visualization. The process of representing data in graphical or pictorial form to make it easier to understand and interpret.
Business Intelligence (BI). The use of technologies, processes, and software to collect, analyze, and present data in order to support decision making and business strategy.
Data Warehousing. A type of database that stores and organizes large amounts of data from multiple sources for analysis and reporting.
Big Data. A large volume of structured and unstructured data that requires specialized tools for storage, analysis, and visualization in order to draw insights from it.

Frequently Asked Questions

What is a Data Analysis Generalist?

A Data Analysis Generalist is a professional that specializes in extracting insights from data through various techniques such as numerical and statistical analysis, data visualization, and predictive modeling.

What skills are needed to become a Data Analysis Generalist?

To become a Data Analysis Generalist, one must have strong analytical and problem-solving skills, be able to interpret data, have knowledge of statistical software, and understand data mining and business intelligence concepts.

What types of data do Data Analysis Generalists work with?

Data Analysis Generalists typically work with structured and unstructured data such as financial records, customer reports, surveys, and web analytics.

What tasks do Data Analysis Generalists typically perform?

Typical tasks for Data Analysis Generalists include data cleaning and preprocessing, data visualization, predictive modeling, and reporting and presenting insights.

How much experience is usually required to become a Data Analysis Generalist?

The amount of experience required to become a Data Analysis Generalist varies depending on the job, but typically a minimum of two to three years of experience in a related field such as data science or analytics is required.

Web Resources

Data Analytics Program | UMass Dartmouth www.umassd.edu
Masters in Data Analytics Online Degree Program www.franklin.edu
UCI Division of Continuing Education (Homepage) - Data Analytics for B ce.uci.edu