Data Manager   

Welcome to the Data Manager Career Academy. This comprehensive program is designed to equip aspiring data managers with the essential skills and knowledge needed to succeed in the dynamic and growing field of data management. Through this hands-on curriculum, you’ll learn how to oversee data operations, ensure data quality, and develop data governance strategies that support data-driven decision-making across organizations.

Throughout this program, you’ll gain expertise in key data management concepts such as data integration, data warehousing, and data security. You’ll learn how to effectively manage large datasets, implement data management frameworks, and use industry-standard tools like SQL, cloud platforms, and data modeling software. You’ll also explore best practices for data governance, privacy, and compliance, while developing skills in leading teams and managing data infrastructure.The Data Manager Career Academy includes the IBM Data Management Professional Certificate and 6 Guided Projects to help master new techniques and programs:

• Database Creation and Modeling using MySQL Workbench
• Aggregate Data in SQL using MySQL Workbench
• Introduction to Data Analysis using Microsoft Excel
• Data Visualization in Tableau: Create Dashboards and Stories
• Data Management with Databricks: Big Data with Delta Lakes
• Data Cleaning in Snowflake: Techniques to Clean Messy Data

The course combines video lectures, interactive labs, and real-world projects to ensure you not only learn but apply your knowledge effectively. With guided assessments and feedback, you will build a robust portfolio that showcases your skills to potential employers.

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Data management is projected to grow 140% by 2030 (IoT Analytics) and is a critical factor for an organization’s competitive edge. Now, more than ever, businesses need skilled data professionals to handle their data effectively.

This IBM Data Manager Professional Certificate equips you with the vital skills and hands-on experience employers seek to competently handle data collection, organization, and protection with accuracy, security, and accessibility while enabling teams to analyze it for decision-making, compliance, and operations.

You’ll gain job-ready skills through hands-on experience using industry-standard tools, including Excel spreadsheets, business intelligence (BI) tools like Tableau, and dashboard design tools such as IBM Cognos. You’ll work with databases including MySQL, PostgreSQL, and MongoDB. Plus, you’ll compare data architectures such as data warehouses, data marts, and data lakes.

You’ll explore core data concepts like relational database management systems (RDBMS) design, integration processes, migration strategies, security protocols, storage, SQL queries, administration, ETL and data pipelines, analysis, and cloud environments.

If you want to launch your data management career quickly, this IBM Professional Certificate gives you the sought-after skills and experience you need to talk about in interviews.

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In this 1-hour long project-based course, you will be able to identify and fully comprehend the basics of the MYSQL workbench and create a new connection to the local server. you will also learn how to create a new database and drop it, create new tables, and delete them. Moreover, You will be able to rename columns of a table, connect tables with each other, and add data to tables. And finally, you will learn how to add columns and apply some features professionally on these columns using some keywords such as PRIMARY KEY, FOREIGN KEY, NOT NULL, AUTO_INCREMENT, and DISTINCT and update the tables with new data. SQL is used by all the big names in tech like Netflix or Airbnb. If you target Google, Facebook, or Amazon, they, of course, have their database systems. But SQL will be there too to query and analyze the data.

This guided project is for beginners in the field of data management data modeling and databases. It provides you with the basics of creating the whole database. It equips you with knowledge of the first steps in modeling.

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In this project you will use MySQL Workbench to write SQL queries that aggregate (group) data. Incorporating aggregate functions like COUNT, SUM, and AVG, your SQL queries will group and summarize data. Data that is aggregated and presented in a logical format makes it a more valuable decision-making tool for users.

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In this project, you will learn the foundation of data analysis with Microsoft Excel using sales data from a sample company. You will learn how to use sorting and filtering tools to reorganize your data and access specific information about your data. You will also learn about the use of functions like IF and VLOOKUP functions to create new data and relate data from different tables. Finally, you will learn how to create PivotTables to summarize and look at comparisons within your data. These skills will help you efficiently perform data analysis on many different types of data and give you the foundation to expand your toolbox as you explore other strategies for data analysis.

In this 2-hour guided project, "Data Management with Databricks: Big Data with Delta Lakes" you will collaborate with the instructor to achieve the following objectives:

1-Create Delta Tables in Databricks and write data to them. Gain hands-on experience in setting up and managing Delta Tables, a powerful data storage format optimized for performance and reliability.

2-Transform a Delta table using Python and leverage SQL to query the data for creating a comprehensive dashboard. Learn how to apply Python-based transformations to Delta Tables, and use SQL queries to extract the necessary insights for building a Supply Chain dashboard.

3-Utilize Delta Lake's merge operation and version control capabilities to efficiently update Delta Tables. Explore the capabilities of Delta Lake's merge operation to perform upserts and other data updates efficiently. Additionally, learn how to leverage Delta Lake's built-in version control to track and access previous versions of Delta Tables as needed.

Throughout a real-world business scenario, you will use Databricks to build an end-to-end data pipeline that integrates various JSON data files and applies transformations, ultimately providing valuable insights and analysis-ready data.

This intermediate-level guided project is designed for data engineers who build data pipelines for their companies using Databricks. In order to be successful in this guided project, you need prior knowledge of writing Python scripts including importing libraries, setting-up variables, manipulating data frames, and using functions. You will also need to be familiar with writing SQL queries such as aggregating, filtering, and joining tables.

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This 2.5 hours-long guided project is designed for business analysts & data engineers eager to learn how to Clean Messy Data in Snowflake Data Platform.

By the end of the project, you will:
-Be able to identify common data quality issues then use SQL String functions to remove unwanted characters and split rows into multiple columns.
-Extract dates from Text fields then use SQL date functions for comparisons and calculations.
-Identify and correct missing and duplicated data then answer business questions using SQL statements.

To achieve these objectives, we will work on a real example from the field, you will play the role of a Data Analyst in the marketing department, who has been tasked with answering a business question, but the customer data they have received presents several data quality challenges.

Note: To be successful in this project you need to have Snowflake beginner knowledge such as Creating a trial account, Databases, Tables, and Virtual Warehouses.

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Use Tableau Web Authoring to create best practice dashboards and stories from data

In this Guided Project, you will:

Develop a best practice interactive dashboard for data exploration, including using dashboard actions for interactivity

Develop a best practice interactive dashboard for reporting, including using filters for interactivity

Develop a best practice data story to put across an argument, justified by data

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