Display working knowledge of Excel for Data Analysis.

Perform basic spreadsheet tasks including navigation, data entry, and using formulas.

Employ data quality techniques to import and clean data in Excel.

Analyze data in spreadsheets by using filter, sort, look-up functions, as well as pivot tables.

Describe the fundamental concepts of statistics and apply them to business and data analytics settings.

Apply data collection, analysis, and interpretation techniques to derive actionable insights for making informed business decisions.

Apply descriptive and inferential analysis methods to derive insights and actionable recommendations from data.

Apply hypothesis testing, regression analysis, and forecasting to support business decision-making processes.

Create basic visualizations such as line graphs, bar graphs, and pie charts using Excel spreadsheets.

Explain the important role charts play in telling a data-driven story. 

Construct advanced charts and visualizations such as Treemaps, Sparklines, Histogram, Scatter Plots, and Filled Map Charts.

Build and share interactive dashboards using Excel and Cognos Analytics.

Describe data, databases, relational databases, and cloud databases.

Describe information and data models, relational databases, and relational model concepts (including schemas and tables). 

Explain an Entity Relationship Diagram and design a relational database for a specific use case.

Develop a working knowledge of popular DBMSes including MySQL, PostgreSQL, and IBM DB2

Analyze data within a database using SQL.

Create a relational database on Cloud and work with tables.

Write SQL statements including SELECT, INSERT, UPDATE, and DELETE.

Build more powerful queries with advanced SQL techniques like views, transactions, stored procedures and joins.

Job-ready data warehousing skills in just 6 weeks, supported by practical experience and an IBM credential.

Design and populate a data warehouse, and model and query data using CUBE, ROLLUP, and materialized views.

Identify popular data analytics and business intelligence tools and vendors and create data visualizations using IBM Cognos Analytics.

How to design and load data into a data warehouse, write aggregation queries, create materialized query tables, and create an analytics dashboard.

Understand Tableau's fundamental concepts, significance in data visualization, diverse product range and key features crucial for data professionals.

Analyze and evaluate the capabilities of Tableau Public as a powerful Business Intelligence (BI) tool for data visualization and analysis.

Implement relationships between data tables, use Tableau calculations for analytics, empower user interaction, and apply filters and highlighting.

Develop expertise in Tableau dashboard design principles, organize visual elements effectively, and apply best practices for interactive dashboards.

Build valuable applied data storage, integration, and migration skills employers need. 

Gain hands-on experience using industry-specific data tools.

Demonstrate you understand data-related best practices and can apply methodologies through industry-standard processes. 

Showcase your ability to solve problems related to data processes that you can talk about in interviews.

Develop and implement effective data privacy and security strategies.

Understand and apply security measures to protect and govern organizational data.

Conduct risk assessments and implement appropriate risk management practices.

Navigate and comply with relevant legal and regulatory compliance requirements.

Integrate valuable applied data management skills employers need for a wide range of data-related roles in a culminating project. 

Gain hands-on experience using industry-specific data tools including Excel, SQL, PostgreSQL, Tableau, etc.

Demonstrate best practices and apply those methodologies through industry-standard processes, data design, governance, security, and reporting.

Showcase your ability to solve problems relevant to working with data that you can discuss with colleagues and prospective employers.

Evaluate your CompTIA Data+ exam readiness with practice exercises using real-world scenarios and statistical methods for data-driven decisions.

Summarize the CompTIA Data+ (DA0-001) certification process, including eligibility criteria, objectives, resources, and associated costs.

Explain core competency areas of the certification, including data mining, manipulation, basic statistical methods, and governance standards.

Identify and apply tools and techniques for analyzing complex datasets to derive insights aligned with business requirements.