Skills you'll gain: Data Management, Big Data, Data Analysis, Exploratory Data Analysis, Probability & Statistics, Distributed Computing Architecture, Machine Learning, Business Analysis, Statistical Programming, Data Science, Graph Theory, Mathematics, Apache, Computer Architecture, Databases, Data Analysis Software, NoSQL, Data Architecture, Machine Learning Algorithms, Business, Data Model, Data Structures, Spreadsheet Software, Data Mining, Python Programming, Data Visualization, SQL, Statistical Machine Learning, Statistical Visualization, Database Application, Information Technology, Cloud Computing, Software As A Service, Applied Machine Learning, Basic Descriptive Statistics, Computer Programming, Correlation And Dependence, Database Administration, Dimensionality Reduction, Feature Engineering, General Statistics, PostgreSQL, Regression, Statistical Analysis, Algorithms, Data Warehousing, Theoretical Computer Science
Beginner · Specialization · 3-6 Months
Skills you'll gain: Apache, Big Data, Data Architecture, Distributed Computing Architecture, Computer Architecture, Data Management, Cloud Applications, Cloud Computing, Data Analysis, Data Warehousing, Database Administration, Databases, DevOps, Extract, Transform, Load, Kubernetes, Network Architecture, Other Programming Languages, SQL
Beginner · Course · 1-3 Months
Skills you'll gain: Business Analysis, Data Analysis, Probability & Statistics, Statistical Analysis, General Statistics, Research and Design, Forecasting, Strategy and Operations, Correlation And Dependence, Financial Analysis, Accounting, Human Resources, Marketing, Operational Analysis, Operations Management, Operations Research, Probability Distribution, Spreadsheet Software, Supply Chain and Logistics, Customer Analysis, Financial Accounting, Market Analysis, Market Research, Basic Descriptive Statistics, Exploratory Data Analysis, Finance, People Management, Performance Management, Regulations and Compliance, Statistical Tests, Talent Management, Collaboration, Communication, Critical Thinking, Data Management, Data Mining, Data Model, Data Visualization, Generally Accepted Accounting Principles (GAAP), HR Tech, Leadership Development, Leadership and Management, MarTech, Marketing Management, Media Strategy & Planning, Microsoft Excel, Organizational Development, Plot (Graphics), Process Analysis, Recruitment, Statistical Programming, Statistical Visualization, Applied Mathematics, Big Data, Business Psychology, Computational Logic, Computer Programming, Computer Programming Tools, Data Analysis Software, Data Structures, Decision Making, Entrepreneurship, Estimation, Mathematics, Network Analysis, People Analysis, People Development, Regression, Sales, Strategy, Theoretical Computer Science
Beginner · Specialization · 3-6 Months
Skills you'll gain: Data Analysis, Data Science, Statistical Programming, Business Analysis, SQL, Spreadsheet Software, Business, Data Visualization, Data Management, R Programming, Exploratory Data Analysis, Statistical Visualization, Communication, Statistical Analysis, Data Analysis Software, Business Communication, Data Structures, Data Visualization Software, Tableau Software, Big Data, Cloud Computing, Collaboration, Conflict Management, Critical Thinking, Customer Analysis, General Statistics, Leadership and Management, Plot (Graphics), Probability & Statistics, Small Data, Algorithms, Application Development, Budget Management, Computational Logic, Computer Architecture, Computer Networking, Computer Programming, Computer Programming Tools, Cryptography, Data Mining, Data Model, Database Administration, Database Design, Databases, Decision Making, Design and Product, Distributed Computing Architecture, Entrepreneurship, Extract, Transform, Load, Feature Engineering, Finance, Full-Stack Web Development, Interactive Data Visualization, Machine Learning, Mathematical Theory & Analysis, Mathematics, Network Security, Other Programming Languages, Problem Solving, Product Design, Programming Principles, Project Management, Research and Design, Security Engineering, Security Strategy, Software Engineering, Software Security, Storytelling, Theoretical Computer Science, Visual Design, Visualization (Computer Graphics), Web Development
Beginner · Professional Certificate · 3-6 Months
Skills you'll gain: Big Data, Data Architecture, Distributed Computing Architecture, Apache, Cloud Computing, Data Analysis Software, NoSQL, Software As A Service, Computer Architecture, Data Analysis, Data Management
Mixed · Course · 1-3 Months
Skills you'll gain: Data Management, Databases, Big Data, Data Structures, SQL, Database Administration, Database Design, Database Theory, Computer Architecture, Data Analysis, Data Warehousing, Database Application, Distributed Computing Architecture, Statistical Programming
Beginner · Course · 1-3 Months
Skills you'll gain: Data Analysis, Data Management, Data Science, Big Data, Databases, NoSQL, Python Programming, SQL, Statistical Programming, Basic Descriptive Statistics, Cloud Computing, Data Mining, Data Structures, Data Visualization, Data Warehousing, General Statistics, Machine Learning, Mathematics, Probability & Statistics, Apache, Business Analysis, Data Visualization Software, Extract, Transform, Load, Leadership and Management, Microsoft Excel, Professional Development
Beginner · Course · 1-3 Months
Big data analytics refers to the application of advanced data analysis techniques to datasets that are very large, diverse (including structured and unstructured data), and often arriving in real time. The ability to process data at this scale is increasingly essential to navigating today’s business world, and it is at the core of important applications such as machine learning, business intelligence, financial engineering, and other software tools to enable data-informed decision-making.
Computer programs have been used to assist with data analysis for decades, but tools like Microsoft Excel and traditional relational database management systems (RDBMS) queried with SQL are not capable of handling today’s high-volume, high-velocity datasets. Instead, today’s data management professionals rely on high-powered data infrastructure designed to work with distributed file systems and cloud computing resources - particularly the open-source Apache Hadoop ecosystem, including high-speed data processing with Apache Spark and distributed SQL engines like Apache Hive.
Organizations of all types and sizes are seeking ways to leverage the possibilities of big data to improve operations through reduced costs and faster decision-making, create new products and services, or advance our knowledge about the world. Big data analytics skills can thus open up a wide range of career opportunities, from working as a “quant” on Wall Street to developing navigation systems for autonomous vehicles to helping to discover more effective medicines and drugs in health science.
Two of the most broadly-applicable roles in this field are data engineers, who build the data infrastructure needed to deliver big data-scale datasets efficiently and reliably, and the data scientists responsible for analyzing them. These roles are in high demand, and are highly-paid as well; according to Glassdoor, data engineers earn an average annual salary of $102,864, and data scientists earn an average annual salary of $113,309.
Absolutely! Data science is one of the most popular topics to learn about on Coursera, and there are a variety of options to build your skills in big data analytics. You can take online courses and Specializations from top-ranked schools like the University of Pennsylvania and the University of California San Diego, as well as leading companies like IBM, PwC, Cloudera, and Google Cloud. And regardless of where you choose to learn from, Coursera gives you the ability to access course materials and complete assignments on a flexible schedule, making this a great fit for students and mid-career professionals alike.
Before you start learning big data analytics, it’s helpful to have an understanding of database management and the fundamentals of how programming languages work. Specifically, experience with SQL, Python, Java, or R can be useful when studying big data analytics. You also may find it beneficial to know how to work with Hadoop and Linux and use basic math and statistics. Additionally, strong analytical skills and a curiosity about playing with data come in handy when you learn big data analytics.
The right people for roles in big data analytics are inquisitive problem solvers who like working with numbers and using statistics to sort through large amounts of data. They typically have work experience or coursework in high-level math or computer programming. A background in behavioral analysis can also be useful for roles in big data analytics because individuals often seek to understand or predict what influences the behavior represented by data. Big data analysts may often need soft skills, such as communication and collaboration skills they use when explaining what they see in the data and working with team members on projects.
If you like working with numbers and are comfortable using statistical techniques, learning big data analytics may be right for you. The amount of data collected on a daily basis is already massive and continues to grow, so organizations need analysts who can curate and prepare data for businesses, governments, and other groups to use. Learning big data analytics may interest you if you possess strong analytical and problem-solving skills and want to apply those skills to sorting and analyzing data to find what’s useful for a client. You may be able to use the knowledge you gain to land an internship or seek a career in data science filling roles in a variety of industries.