IBM Data Management

Spreadsheet tools like Excel are an essential tool for working with data - whether for data analytics, business, marketing, or research. This course is designed to give you a basic working knowledge of Excel and how to use it for analyzing data. This course is suitable for those who are interested in pursuing a career in data analysis or data science, as well as anyone looking to use Excel for data analysis in their own domain. No prior experience with spreadsheets or coding is required - all you need is a device with a modern web browser and the ability to create a Microsoft account to access Excel online at no cost. If you have a desktop version of Excel, you can also easily follow along with the course. Throughout this course, you'll gain valuable experience working with data sets and spreadsheets. We'll start by introducing you to spreadsheets like Microsoft Excel and Google Sheets, and show you how to load data from multiple formats. From there, you'll learn how to perform basic data wrangling and cleansing tasks using functions, and expand your knowledge of data analysis through the use of filtering, sorting, and pivot tables. There is a strong focus on practice and applied learning in this course. With each lab, you'll have the opportunity to manipulate data and gain hands-on experience using Excel. You'll learn how to clean and format your data efficiently, and convert it into a pivot table to make it more organized and readable. The final project will allow you to showcase your newly acquired data analysis skills by working with real data sets and spreadsheets. By the end of this course, you'll have a solid foundation in using Excel for data analysis. You'll have worked with multiple data sets and spreadsheets, and will have the skills and knowledge needed to effectively clean and analyze data without having to learn any code. So let's get started!

Learn how to create data visualizations and dashboards using spreadsheets and analytics tools. This course covers some of the first steps for telling a compelling story with your data using various types of charts and graphs. You'll learn the basics of visualizing data with Excel and IBM Cognos Analytics without having to write any code. You'll start by creating simple charts in Excel such as line, pie and bar charts. You will then create more advanced visualizations with Treemaps, Scatter Charts, Histograms, Filled Map Charts, and Sparklines. Next you’ll also work with the Excel PivotChart feature as well as assemble several visualizations in an Excel dashboard. This course also teaches you how to use business intelligence (BI) tools like Cognos Analytics to create interactive dashboards. By the end of the course you will have an appreciation for the key role that data visualizations play in communicating your data analysis findings, and the ability to effectively create them. Throughout this course there will be numerous hands-on labs to help you develop practical experience for working with Excel and Cognos. There is also a final project in which you’ll create a set of data visualizations and an interactive dashboard to add to your portfolio, which you can share with peers, professional communities or prospective employers.

Start your journey in one of the fastest growing professions today with this beginner-friendly Data Engineering course! You will be introduced to the core concepts, processes, and tools you need to know in order to get a foundational knowledge of data engineering. as well as the roles that Data Engineers, Data Scientists, and Data Analysts play in the ecosystem. You will begin this course by understanding what is data engineering as well as the roles that Data Engineers, Data Scientists, and Data Analysts play in this exciting field. Next you will learn about the data engineering ecosystem, the different types of data structures, file formats, sources of data, and the languages data professionals use in their day-to-day tasks. You will become familiar with the components of a data platform and gain an understanding of several different types of data repositories such as Relational (RDBMS) and NoSQL databases, Data Warehouses, Data Marts, Data Lakes and Data Lakehouses. You’ll then learn about Big Data processing tools like Apache Hadoop and Spark. You will also become familiar with ETL, ELT, Data Pipelines and Data Integration. This course provides you with an understanding of a typical Data Engineering lifecycle which includes architecting data platforms, designing data stores, and gathering, importing, wrangling, querying, and analyzing data. You will also learn about security, governance, and compliance. You will learn about career opportunities in the field of Data Engineering and the different paths that you can take for getting skilled as a Data Engineer. You will hear from several experienced Data Engineers, sharing their insights and advice. By the end of this course, you will also have completed several hands-on labs and worked with a relational database, loaded data into the database, and performed some basic querying operations.

Are you ready to dive into the world of data engineering? In this beginner level course, you will gain a solid understanding of how data is stored, processed, and accessed in relational databases (RDBMSes). You will work with different types of databases that are appropriate for various data processing requirements. You will begin this course by being introduced to relational database concepts, as well as several industry standard relational databases, including IBM DB2, MySQL, and PostgreSQL. Next, you’ll utilize RDBMS tools used by professionals such as phpMyAdmin and pgAdmin for creating and maintaining relational databases. You will also use the command line and SQL statements to create and manage tables. This course incorporates hands-on, practical exercises to help you demonstrate your learning. You will work with real databases and explore real-world datasets. You will create database instances and populate them with tables and data. At the end of this course, you will complete a final assignment where you will apply your accumulated knowledge from this course and demonstrate that you have the skills to: design a database for a specific analytics requirement, normalize tables, create tables and views in the database, load and access data. No prior knowledge of databases or programming is required. Anyone can audit this course at no-charge. If you choose to take this course and earn the Coursera course certificate, you can also earn an IBM digital badge upon successful completion of the course.

Much of the world's data lives in databases. SQL (or Structured Query Language) is a powerful programming language that is used for communicating with and manipulating data in databases. A working knowledge of databases and SQL is a must for anyone who wants to start a career in Data Engineering, Data Warehousing, Data Analytics, Data Science or Business Intelligence. The purpose of this course is to help you learn and apply foundational and intermediate knowledge of the SQL language, and become familiar with many relational database (RDBMS) concepts along the way. You will start with performing basic Create, Read, Update and Delete (CRUD) operations using CREATE, SELECT, INSERT, UPDATE and DELETE statements. You will then learn to filter, order, sort, and aggregate data. You will work with functions, perform sub-selects and nested queries, as well as JOIN data in multiple tables. You will also work with VIEWS, transactions and create stored procedures. The emphasis in this course is on hands-on, practical learning. As such, you will work with real database systems, use real tools, and real-world datasets. You will create a database instance in the cloud. Through a series of hands-on labs, you will practice building and running SQL queries. At the end of the course you will apply and demonstrate your skills with a final project. The SQL skills you learn in this course will be applicable to a variety of RDBMSes such as MySQL, PostgreSQL, IBM Db2, Oracle, SQL Server and others. No prior knowledge of databases, SQL or programming is required, however some basic data literacy is beneficial.

This course is aimed at familiarizing Data and Business professionals with the basic concepts of statistical analysis and methods used for data-driven decision-making. After completing this course, you will be able to apply descriptive and inferential analysis methods, use data visualization methods to communicate data, apply concepts of probability in real-life scenarios, and apply regression techniques to predict trends. The course takes a hands-on approach to statistical analysis using Microsoft Excel and uses examples to illustrate the concepts to help you gain the foundational knowledge of statistical techniques needed to solve business intelligence (BI) problems. A hands-on project will provide you an opportunity to apply the concepts to a real-life scenario involving data-driven decision-making and an understanding of basic statistical thinking and reasoning. This course is suitable for professionals or students who aspire to embark on a career in the BI or Data Analytics fields by equipping them with the crucial skills and knowledge in statistical analysis. It is expected that learners be familiar with Excel/spreadsheet basics and high school mathematics prior to starting this course.

This short course is designed for anyone seeking to unlock the full potential of Tableau Public, a leading data visualization tool. Starting from the fundamentals, you will progress through each module, gaining hands-on experience in importing, exploring, and visualizing data. From creating basic visualizations to designing interactive dashboards and compelling stories, this course covers it all. You will explore real-time data updates, ensuring adaptability, and master the art of storytelling in data visualization, crafting effective Tableau stories with customization and adherence to best practices. Practical exercises based on real-world scenarios throughout the course ensure the knowledge you gain isn’t just theoretical but aligns with the skills employers are looking for. Start building the foundation to harness the power of Tableau for effective data visualization and analysis today.

Whether you’re an aspiring data engineer, data architect, business analyst, or data scientist, strong data warehousing skills are a must. With the hands-on experience and competencies, you gain on this course, your resume will catch the eye of employers and power up your career opportunities. A data warehouse centralizes and organizes data from disparate sources into a single repository, making it easier for data professionals to access, clean, and analyze integrated data efficiently. This course teaches you how to design, deploy, load, manage, and query data warehouses, data marts, and data lakes. You’ll dive into designing, modeling, and implementing data warehouses, and explore data warehousing architectures like star and snowflake schemas. You’ll master techniques for populating data warehouses through ETL and ELT processes, and hone your skills in verifying and querying data, and utilizing concepts like cubes, rollups, and materialized views/tables. Additionally, you’ll gain valuable practical experience working on hands-on labs, where you’ll apply your knowledge to real data warehousing tasks. You’ll work with repositories like PostgreSQL and IBM Db2, and complete a project that you can refer to in interviews.

Data integration, data storage, and data migration are core skills for a data professionals. With data management projected to grow by 140% by 2030 (IoT Analytics), these skills are in hot demand! As part of the IBM Data Manager Professional Certificate, this Data Integration, Data Storage, and Data Migration Strategies gives aspiring data managers the essential skills employers are looking for. During this course, you’ll learn best practices and processes in these three key areas—data integration, storage, and migration. You’ll investigate data integration and automate data aggregation from disparate sources into a single view to make it useful for analysis. You’ll explore data storage methods and processes to ensure your data is organized. Plus, you’ll learn data migration processes businesses use to upgrade their legacy systems and infrastructure with minimal disruption to other business operations. If you’re looking to enhance your resume with the essential skills, a data manager needs to catch an employer’s eye, enroll today and boost your career opportunities in just three weeks!

In this capstone course, you’ll demonstrate your ability to solve problems relevant to data-related roles, which you can then showcase in your portfolio and share with prospective employers. You will apply the skills you’ve learned throughout this data management program with this hands-on culminating project. The project provides you the opportunity to solidify your proficiency when working with various aspects of data and integrate them into a single project. You’ll apply many industry-specific tools and industry-standard best practices to a real-world-inspired scenario. As part of this process, you utilize relational databases and SQL queries. You’ll also manipulate data using spreadsheets and BI tools to create visualizations and a dashboard to readily communicate your data insights. We recommend that you complete all the previous courses in this Professional Certificate before starting this course.

Whether you’re an aspiring data engineer, data architect, business analyst, or data scientist, a strong foundation in data security is crucial for any data management professional. By gaining practical experience and comprehensive knowledge, you will strengthen your resume and unlock exciting career opportunities in the dynamic field of data security and protection. This course provides insight into data privacy, security, and governance. You will learn to implement effective strategies for protecting sensitive information while identifying and mitigating various cyberthreats. You’ll explore encryption techniques, access control management, and incident response planning. The course also covers data architecture and governance, where you will develop frameworks for maintaining data quality and integrity. Additionally, learner will learn about risk management and compliance, focusing on essential regulations to safeguard data and foster organizational trust. You will reinforce the concepts learned in the course through hand-on labs, activities, and case studies. To enhance your resume with the essential skills for a data-oriented career and attracting the attention of potential employers, enroll today!