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PG Applied Data Science

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PG Applied Data Science

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PG Applied Data Science

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PG Applied Data Science

Program Overview

Certification Program in Applied Data Science

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Business / Data Analytics

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Machine Learning

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Machine Leanring

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Deep Learning & Artificial Intelligence

Certification Programs

Program Overview

Certification Program in Applied Data Science

FOUNDATIONAL

Business / Data Analytics

FOUNDATIONAL

Machine Learning

Advance

Machine Leanring

Advance

Deep Learning & Artificial Intelligence

Career Oriented

Career Acceleration Program

Career Acceleration Program

Career Oriented

Career Acceleration Program

Business Analyst vs Data Analyst

Although data analyst and business analyst share some tasks and abilities, they may have different roles within an organization. Here are some essential details to help explain why there can occasionally be misunderstandings between the two jobs, as well as why they differ significantly:

Source: Data Analyst vs Business Analyst

Skills That Drive Success

Data Handling:

Working with data to extract insights that might support the company in making wise decisions is a must for both professions.

For the extraction, modification, and analysis of data, they employ comparable instruments and methods.

Analytical Skills:

To analyze data and provide insights that may be put to use, both require excellent analytical abilities.

They must be skilled in the use of data visualization software to properly present findings.

Reporting:

To provide stakeholders with data insights, both responsibilities entail developing reports and dashboards.

Navigating Analyst Roles: Data and Business

Primary Focus:

Data Analyst:

Mainly focuses on data analysis to find patterns, trends, and insights.

More analytical and technically focused; frequently works with big datasets, statistical analysis, and even machine learning.

Business Analyst:

Focuses on gathering requirements, comprehending business wants, and enhancing business procedures.

More commercial, collaborating closely with stakeholders to comprehend their demands and convert them into technological specifications.

Typical Responsibilities:

Data Analyst:

Carry out data transformation, cleansing, and analysis.

Create and manage dashboards, visualizations, and data models.

Analyse complicated datasets statistically and understand them.

Business Analyst:

Ask stakeholders for requirements, then record business processes.

Create project blueprints and business cases.

Serve as a point of contact for development or IT teams and business departments.

Source: Responsibilities of Data Analyst

Skill Sets:

Data Analyst:

Strong proficiency in statistical analysis, Tableau, Power BI, and Python/R for data visualization.

Familiarity with ETL procedures, database administration, and potentially machine learning.

Business Analyst:

Strong grasp of project management, requirements analysis, and business processes.

Proficiency in requirements-gathering approaches, business analysis tools (e.g., BPMN), and potentially some understanding of agile processes.

Source: Key Skills

End Goals:

Data Analyst:

Provide thorough data insights to support corporate strategy and decision-making.

Often works on several data-related initiatives in several divisions.

Business Analyst:

Make that the technological solutions being used fully comprehend and satisfy the business needs.

Put your attention on streamlining business procedures and enabling efficient communication between technology teams and business divisions.

Data Insight vs. Business Insight: Analyst Roles

Due to resource limitations, there may be a large overlap between the tasks of business analysts and data analysts in certain organizations, particularly smaller ones. These positions are more defined in larger companies, with specific duties and responsibilities assigned to each.

While there are some similarities between business analysts and data analysts, especially when it comes to using data and analytical abilities, each role’s main objectives, usual tasks, skill sets, and areas of concentration are different. Business analysts are more concerned with comprehending and enhancing business processes via efficient requirements management and communication than data analysts are with the technical components of data analysis. It will become clearer what unique contributions each function contributes to an organization if these distinctions are understood. The importance of data in business decision-making is driving up demand, which speaks well for data analysts and business analysts in the future. Tools and technology will progress, allowing for specialization and a move towards more strategic and value-added jobs for both occupations. Maintaining relevance and efficacy in these changing positions will need constant learning and adjustment to new techniques and technology.