IBM Business Intelligence (BI) Analyst

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.

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 provides a comprehensive introduction to business intelligence (BI), its key concepts, components, and the benefits and challenges of implementing BI solutions. It also discusses career opportunities and roles available in the BI arena and the skills and qualifications required. You will also gain insight into the data ecosystem, BI analytics landscape, data repositories, and the extract, transform, and load (ETL) process. Additionally, you will be introduced to the role of statistical analysis in mining and visualizing data to identify patterns and trends and how to weave a compelling story with data. The course offers practical exposure with hands-on activities and a final project that enables you to apply your knowledge in real-world scenarios. This specialized program is tailored for individuals interested in pursuing a career as a BI analyst, and no prior data analytics experience or degree is required to take this course.

This advanced Tableau course covers a broad variety of topics to provide you with advanced analytics and data visualization skills. The course walks you through connecting Tableau to SQL databases, creating data linkages, and creating hierarchies for effective analysis, starting with data connectivity and modeling. You will work with sophisticated modeling approaches, execute computations, and optimize data models for performance. The course has a strong emphasis on controlling data granularity, utilizing calculated fields, and investigating expressions for ‘Level of Detail’ in complicated analytics. Topics include effective data transfer, tooltips, hierarchical navigation, and creating user-friendly interfaces. By incorporating interactivity through actions and linking between dashboards, you’ll create seamless data journeys that empower users to explore and analyze information effortlessly. Throughout the course, you will have opportunities to practice what you have learned. Hands-on labs and projects are inspired from real-world scenarios, to equip you with the advanced, practical Tableau skills that employers seek in today’s job market.

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.

This course marks the culmination of the IBM BI Analyst Professional Certificate. It provides you an opportunity to apply data analysis techniques acquired in the previous courses to real-world datasets, allowing you to extract meaningful insights and discover patterns. Throughout the course, you will work with various tools such as Excel for data cleaning and basic visualization, PostgreSQL and pgAdmin for data querying and complex analysis, and Tableau for data visualizations (learners may opt for other data visualization applications such as Cognos or Looker instead). At the end of the course, you will present and highlight the outcomes of the BI Analyst project, emphasizing their impact on decision-making and business performance. Upon completion of the course, you will have a variety of artifacts showcasing your business intelligence skills to include in your portfolio.

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.