Data Analyst
This is an introductory course on data analytics, designed to prepare students for a career as a junior
data analyst.
- Businesses recognize the value of data analytics for competitiveness and are hiring and upskilling
people to drive their initiatives.
- There is a significant supply and demand mismatch for skilled data analysts, making it a highly
sought-after and well-paid profession.
- Students can choose to master data analytics as a career or use it as a stepping stone to other data
professions.
- The course covers core concepts, processes, and tools needed for data analytics, including data
gathering, wrangling, mining, analysis, and visualization.
- Students will learn about the data ecosystem and the fundamentals of data analysis, as well as career
options and learning paths to consider.
- The data ecosystem includes a variety of structured and unstructured data sets from diverse and
dynamic sources, which need to be acquired, organized, cleaned, and optimized for access by end-
users.
- Key challenges in data analytics include data management, working with data repositories, and
providing interfaces, APIs, and applications to meet end-users' specific needs.
The introductory course on data analytics is designed to prepare individuals for a career as a junior
data analyst. Businesses today recognize the untapped value in data and data analytics as a crucial
factor for business competitiveness, resulting in a significant supply and demand mismatch in skilled
data analysts, making it a highly sought after and well-paid profession. The course introduces
individuals to the core concepts, processes, and tools needed to gain entry into data analytics or
strengthen their current role as a data-driven decision-maker. It equips individuals with an
understanding of the data ecosystem and the fundamentals of data analysis, such as data gathering,
wrangling, mining, analysis, and data visualization. The course also provides insight into a day in the
life of a data analyst, career options, and learning paths to consider.
Data is available in a variety of structured and unstructured data sets residing in text, images, videos,
click streams, user conversations, social media platforms, IoT devices, real-time events, legacy
databases, and data sourced from professional data providers and agencies. The first step is to pull a
copy of the data from the original sources into a data repository, followed by organizing, cleaning up,
and optimizing the data for access by end-users. The key challenges at this stage involve data
management and working with data repositories that provide high availability, flexibility, accessibility,
and security. Finally, business stakeholders, applications programmers, analysts, and data science use
This is an introductory course on data analytics, designed to prepare students for a career as a junior
data analyst.
- Businesses recognize the value of data analytics for competitiveness and are hiring and upskilling
people to drive their initiatives.
- There is a significant supply and demand mismatch for skilled data analysts, making it a highly
sought-after and well-paid profession.
- Students can choose to master data analytics as a career or use it as a stepping stone to other data
professions.
- The course covers core concepts, processes, and tools needed for data analytics, including data
gathering, wrangling, mining, analysis, and visualization.
- Students will learn about the data ecosystem and the fundamentals of data analysis, as well as career
options and learning paths to consider.
- The data ecosystem includes a variety of structured and unstructured data sets from diverse and
dynamic sources, which need to be acquired, organized, cleaned, and optimized for access by end-
users.
- Key challenges in data analytics include data management, working with data repositories, and
providing interfaces, APIs, and applications to meet end-users' specific needs.
The introductory course on data analytics is designed to prepare individuals for a career as a junior
data analyst. Businesses today recognize the untapped value in data and data analytics as a crucial
factor for business competitiveness, resulting in a significant supply and demand mismatch in skilled
data analysts, making it a highly sought after and well-paid profession. The course introduces
individuals to the core concepts, processes, and tools needed to gain entry into data analytics or
strengthen their current role as a data-driven decision-maker. It equips individuals with an
understanding of the data ecosystem and the fundamentals of data analysis, such as data gathering,
wrangling, mining, analysis, and data visualization. The course also provides insight into a day in the
life of a data analyst, career options, and learning paths to consider.
Data is available in a variety of structured and unstructured data sets residing in text, images, videos,
click streams, user conversations, social media platforms, IoT devices, real-time events, legacy
databases, and data sourced from professional data providers and agencies. The first step is to pull a
copy of the data from the original sources into a data repository, followed by organizing, cleaning up,
and optimizing the data for access by end-users. The key challenges at this stage involve data
management and working with data repositories that provide high availability, flexibility, accessibility,
and security. Finally, business stakeholders, applications programmers, analysts, and data science use
