How To Become a Data Analyst in Kenya consists of different things. Data Analysts are corporate detectives who examine the organization’s data sets in minute detail, so their interpretations highlight critical patterns and trends in the business.
Data analysis is a fast-growing field. The demand for
experienced Data Analysts will only grow worldwide across multiple industries
and domain types, including healthcare, pharmaceuticals, manufacturing,
education, marketing, sales, media, finance, consulting, retail and even real
estate.
What do Data Analysts do?
A Data Analyst would typically need to:
- Retrieve,
gather, clean, and interpret an organisation’s data sets to answer a
question, solve a problem or reach meaningful conclusions
- Collect,
understand and document detailed business requirements, using appropriate
tools and techniques
- Work
with technology teams, management and data scientists to set goals; mine
data from primary and secondary sources
- Design
and carry out surveys; analyse survey data; liaise with internal and
external clients to understand data content thoroughly
- Clean
and dissect data to remove unnecessary information; identify areas to
increase the efficiency and automation of processes
- Identify,
evaluate and implement external services and tools to support data
validation and cleansing
- Analyse
and interpret results using statistical tools and techniques; produce and
track key performance indicators; pinpoint trends and patterns in data
sets
- Monitor
and audit data quality; track, analyse and interpret complex data sets
relating to the employer’s business
- Analyse
market research, opinion polls and trends in consumer feedback to help the
organisation make sound business decisions
- Prepare
reports for internal and external audiences, using business analytics
reporting tools
- Create
data dashboards, graphs and visualisations; provide sector and competitor
benchmarking
- Mine
and analyse large data sets, identify new opportunities for process
improvement and present them successfully to management
- Establish
records management processes and policies; set up and maintain automated
data processes; develop and support reporting processes
- Fix
code problems and data-related issues
Free Data Analysis Online Courses
- Data
Analytics – Mining and Analysis of Big Data – Learn how to
analyse big data using mining and clustering techniques, in this free online big data
analytics course.
- Data
Science – Visualizing Data and Exploring Models – Learn about
data science techniques, applying visualizations to display data, feature
engineering methods, and more!
- Diploma
in Using Python for Data Science –
Learn how to use your basic Python knowledge and turn it into a career in data science.
Recommended Work Experience
A period of supervised experience in the form of an
internship or placement during your degree is an essential prerequisite for
most Data Analyst positions.
Previous work experience as an administrative assistant or
customer service representative will also help. Consulting firms, government
agencies, media, and telecommunications companies offer graduate schemes that
facilitate access to entry-level roles.
Read about the profession and interview/job shadow experts
working in data analytics to prove your commitment to course providers and
prospective employers.
Recommended Qualifications
Most Data Analysts have a bachelor’s degree in business
information systems, computer science, economics, information management,
mathematics and statistics.
Although it is not usually required, a sizeable number is
increasingly opting for a master’s degree in data science, business analytics,
data science, and big data. Some universities offer an integrated
five-year-long Masters program, combining a degree and masters course. A few
employers may ask for a doctorate in a relevant subject.
Focus on mathematics, economics, statistics and computer
science in high school to facilitate entry to accredited colleges.
Recommended Skills
Data Analysts need excellent research, problem-solving,
mathematical, analytical, collaborative and reporting skills. Knowledge of
various programming languages, data analysis tools, data enrichment techniques,
open-source data analytics, data protection issues, industry-specific databases
and data sets and the ability to prioritise tasks will make you a force to
contend with.