What are big data analytics, and why are they important to learn about?

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.

What kinds of careers can I get with a background in big data analytics?

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.

Can I learn about big data analytics by taking online courses on Coursera?

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.

What skills or experience do I need to already have before learning about big data analytics?

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.

What kind of people are most suited for work in 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.

How do I know if learning big data analytics is right for me?

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.

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Результатов для запроса ''big data analytics': 403

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Yonsei University
Spatial Data Science and Applications
Получаемые навыки: Network Analysis, Geovisualization, Spatial Data Analysis, Distributed Computing Architecture, Geographic Information System, Data Management, Data Analysis, Big Data, Spatial Analysis, Analysis, Data Visualization, Computer Architecture, Apache, Mathematics
4.4
(рецензий: 448)
Intermediate · Course · 1-3 Months
IBM Skills Network
NoSQL, Big Data, and Spark Foundations
Получаемые навыки: Algorithms, Apache, Big Data, Cloud Computing, Computational Thinking, Computer Architecture, Computer Networking, Computer Programming, Data Management, Database Theory, Databases, Distributed Computing Architecture, Extract, Transform, Load, Graph Theory, IBM Cloud, Kubernetes, Machine Learning, Machine Learning Algorithms, Mathematics, Network Architecture, NoSQL, SQL, Statistical Programming, Theoretical Computer Science
4.2
(рецензий: 199)
Beginner · Specialization · 3-6 Months
IBM Skills Network
IBM Data Analyst
Получаемые навыки: Algebra, Apache, Big Data, Business Analysis, Computational Logic, Computer Programming, Computer Programming Tools, Correlation And Dependence, Data Analysis, Data Analysis Software, Data Management, Data Mining, Data Structures, Data Visualization, Data Visualization Software, Data Warehousing, Database Administration, Database Application, Databases, Econometrics, Exploratory Data Analysis, Extract, Transform, Load, General Statistics, Geovisualization, Leadership and Management, Machine Learning, Mathematical Theory & Analysis, Mathematics, Microsoft Excel, NoSQL, Operating Systems, Plot (Graphics), Probability & Statistics, Professional Development, Python Programming, Regression, Regression Analysis, SQL, Spreadsheet Software, Statistical Analysis, Statistical Machine Learning, Statistical Programming, Statistical Visualization, System Programming, Theoretical Computer Science
4.6
(рецензий: 52.3k)
Beginner · Professional Certificate · 3-6 Months
IBM Skills Network
IBM Data Engineering
Получаемые навыки: Algorithms, Apache, Big Data, Business Analysis, Cloud Computing, Cloud Engineering, Computational Logic, Computational Thinking, Computer Architecture, Computer Networking, Computer Programming, Computer Programming Tools, Data Architecture, Data Engineering, Data Management, Data Model, Data Visualization, Data Visualization Software, Data Warehousing, Database Administration, Database Application, Database Design, Database Theory, Databases, DevOps, Distributed Computing Architecture, Extract, Transform, Load, Graph Theory, Hardware Design, IBM Cloud, Kubernetes, Leadership and Management, Machine Learning, Machine Learning Algorithms, Mathematical Theory & Analysis, Mathematics, Microarchitecture, Network Architecture, Network Security, NoSQL, PostgreSQL, Professional Development, Programming Principles, Project Management, Python Programming, SQL, Security Engineering, Security Strategy, Software Architecture, Software Engineering, Statistical Programming, Strategy and Operations, Theoretical Computer Science
4.6
(рецензий: 35.8k)
Beginner · Professional Certificate · 3-6 Months
IBM Skills Network
IBM Data Analytics with Excel and R
Получаемые навыки: Advertising, Analysis, Apache, Big Data, Business Analysis, Communication, Computational Logic, Computer Programming, Data Analysis, Data Analysis Software, Data Management, Data Mining, Data Structures, Data Visualization, Data Visualization Software, Data Warehousing, Databases, Extract, Transform, Load, General Statistics, Interactive Data Visualization, Leadership and Management, Marketing, Microsoft Excel, NoSQL, Operating Systems, Plot (Graphics), Probability & Statistics, Professional Development, Programming Principles, R Programming, Regression, SQL, Spreadsheet Software, Statistical Analysis, Statistical Programming, Statistical Visualization, System Programming, Theoretical Computer Science
4.7
(рецензий: 10.7k)
Beginner · Professional Certificate · 3-6 Months
IBM Skills Network
Data Analysis and Visualization Foundations
Получаемые навыки: Analysis, Apache, Big Data, Business Analysis, Computer Programming, Data Analysis, Data Analysis Software, Data Management, Data Mining, Data Structures, Data Visualization, Data Visualization Software, Data Warehousing, Databases, Extract, Transform, Load, General Statistics, Leadership and Management, Microsoft Excel, NoSQL, Operating Systems, Plot (Graphics), Professional Development, Spreadsheet Software, Statistical Visualization, System Programming
4.7
(рецензий: 10.4k)
Beginner · Specialization · 3-6 Months

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10 самых популярных курсов по запросу big data analytics

Foundations of marketing analytics: ESSEC Business School
Ubiquitous Learning and Instructional Technologies: University of Illinois at Urbana-Champaign
Spatial Data Science and Applications: Yonsei University
Generando un Data Lake House con Azure Synapse Analytics: Coursera Project Network
Big Data Analysis Deep Dive: Alibaba Cloud Academy
Working with BigQuery: Coursera Project Network
NoSQL, Big Data, and Spark Foundations: IBM Skills Network
Introdução ao Big Data: Fundação Instituto de Administração
IBM Data Analyst: IBM Skills Network
IBM Data Engineering: IBM Skills Network

Навыки, которые вы можете получить здесь: Machine Learning

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Часто задаваемые вопросы на тему Big Data Analytics

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.‎

Часто задаваемые вопросы предоставляются в ознакомительных целях. Учащимся рекомендуется дополнительно убедиться в том, что интересующие их курсы и другие материалы соответствуют их личным, профессиональным и финансовым потребностям.