Big Data Core Concepts: beginner Big Data 2019
Expertise:
Technology:
- 2 Courses | 1h 15m 40s
- 8 Books | 27h 41m
- Includes Lab
- 1 Course | 1h 2m 19s
- 1 Book | 5h 25m
- Includes Lab
- 5 Courses | 3h 33m 9s
- 2 Books | 7h 1m
- Includes Lab
- 7 Courses | 5h 13m 50s
- 8 Books | 44h 19m
- Includes Lab
Thanks to modern computers, massive amounts of data can be analyzed for trends and patterns. Discover the various facets and tools of big data.
GETTING STARTED
Big Data Concepts: Getting to Know Big Data
-
1m 35s
-
3m 6s
COURSES INCLUDED
Managing Big Data Operations
Big data has changed the way we think about data systems. Explore the challenges being faced as a result of big data operations, as well as big data monitoring tools, orchestrations, and performance modeling.
11 videos |
38m
Assessment
Badge
Quality & Security of Big Data Operations
To be of any use, data must be accessible, accurate, and secure. Examine methods for application and performance testing, as well as data testing, prevention, and preservation.
10 videos |
37m
Assessment
Badge
COURSES INCLUDED
Securing Big Data Streams
Learners can explore security risks related to modern data capture, data centers, and processing methods, such as streaming analytics, in this 13-video course. As the value of a company's data increases, the same data have become more and more valuable to hackers and other criminals. You will learn up-to-date techniques and tools employed to mitigate security risks, and best practices related to securing big data, including cloud data, trust, and encryption. Begin with an overview of common security concerns for big data and streaming data, as well as concerns related to NoSQL (non-structured query language), distributed processing frameworks, and flaws related to data mining and analytics. Then explore how to secure big data; explore streaming data and data in motion; and see how end-point devices are secured by using validation and filtering, as well as how to use encryption to secure data at rest. In the concluding exercise, practice what you have learned by describing key big data security concerns, key streaming data security concerns, and how end-point devices are secured.
13 videos |
1h 2m
Assessment
Badge
COURSES INCLUDED
Big Data Concepts: Getting to Know Big Data
Big data analytics has become an essential part of any business dealing with the digital world. The ability to collect large amounts of data and turn it into insights has transformed the world's business landscape. To properly manage projects using such technologies, leaders should at least have a foundational understanding of big data. Use this course to get to grips with the necessary concepts and terminologies you'll need when discussing big data projects. Learn about the primary sources and characteristics of big data. Then, dive into the world of big data analytics - exploring its main advantages, use cases, and significant challenges. When you've finished this course, you'll be able to speak about data-related projects, discussing relevant data infrastructures and architectures confidently.
12 videos |
38m
Assessment
Badge
Big Data Concepts: Big Data Essentials
Big data analytics, collecting vast amounts of data and transforming it into insights, drives major business decisions everywhere. Managers, decision-makers, data technicians, and data enthusiasts alike benefit from knowing how various systems and technologies are used in big data projects. Use this course to progress from a foundational comprehension of big data analytics to grasping more advanced concepts, like parallel and distributed computing systems and horizontal and vertical scaling. Take an in-depth look at Hadoop's main components and characteristics and how it's used for big data analytics. Then, delve into the various kinds of storage systems used in big data. Upon completing this course, you'll have a greater comprehension of the tools and methods used to execute big data projects.
12 videos |
40m
Assessment
Badge
Techniques for Big Data Analytics
Big data analytics provides a way to turn the vast amounts of data available in today's digital world into valuable insights. For this reason, big data analytics techniques have taken a central place in many businesses' IT infrastructure. These comprise complex processes and multiple stack layers that allow you to transform raw data into visualizations that demonstrate trends or other phenomena. Use this course to explore the basic principles and techniques of big data analytics in a business context. Go through each step of data processing to fully comprehend the big data analytics pipeline. Furthermore, explore various use cases of big data analytics through real-world examples. When you're done with this course, you'll have a foundational comprehension of some of the technologies behind big data and how these can drive business decisions for the better.
12 videos |
34m
Assessment
Badge
Spark for High-speed Big Data Analytics
Spark is an open-source, massively parallel, in-memory solution that allows you to run big data analytics pipelines at high speed. Use this course to learn how Apache Spark works and gain an understanding of its architecture. As you progress, investigate the industry-leading examples of Uber and Alibaba to recognize how Spark can add business value to data in many industry types. Moving along, compare the functionality of Spark and Hadoop in relation to use cases, identifying when using Spark is most advantageous. Finally, explore fundamental Spark characteristics, optimization techniques, and best practices. When you've completed this course, you'll have a solid theoretical understanding of how and when to use Apache Spark for specific big data analytics tasks.
12 videos |
45m
Assessment
Badge
Organizational IT Trends, Analytics, and Application Development
IT and business trends can have a serious impact on an organization's growth and direction. Key areas that could be impacted include business models, employee experience, business processes, and customer experience. In this course, you'll learn how IT Trends can impact organizations, and how they can gauge if they are ready for change. You'll also explore key questions organizations can ask when determining big data analytics capabilities, and discover the value of data in decision making, performance, and growth. You'll also learn about the possible impact of application development in an organization, and learn how organizations can leverage it. Lastly, discover how application development is the process and practice of designing, developing, deploying, and operating highly available and cost-effective software or applications. This course was originally created by Global Knowledge (GK).
15 videos |
53m
Badge
SHOW MORE
FREE ACCESS
COURSES INCLUDED
Introduction to Hadoop
Several tools are available for working with big data. Many of the tools are open-source and Linux-based. Explore the fundamentals of Apache Hadoop, including distributed computing, design principles, HDFS, Yarn, MapReduce, and Spark.
7 videos |
27m
Assessment
Badge
Teams & Projects
Big data requires a holistic approach and a change to regular working practices. Discover the way teams work in big data organizations, as well as some projects and use cases for big data.
12 videos |
47m
Assessment
Badge
Use Cases, Opportunities, & Challenges
Big data requires a holistic approach and a change to regular working practices. Explore use cases for big data, as well as challenges and opportunities that big data presents.
11 videos |
47m
Assessment
Badge
Engineering Perspectives
Big data is a term for data sets so large that traditional data processing applications can't be used to perform meaningful analysis. Explore some of the engineering challenges of big data and how some companies have discovered solutions.
10 videos |
55m
Assessment
Badge
Corporate Leadership Perspective
Big data leaders must be able to show how big data generates value and how investments should be targeted. Discover how to create a governance strategy, examine security concerns, and how this will impact human resources.
10 videos |
49m
Assessment
Badge
Strategic Planning
To adopt big data, senior leadership must be able to establish priorities and ensure acceptance by the front line. Discover scaling up to scaling out, different analytical models, and how to secure funding for data initiatives.
10 videos |
52m
Assessment
Badge
Big Data Sales Perspective
Big data allows salespeople to adopt data-driven methodologies to target high-value prospects. Explore the differences between big data and data science, including different algorithms and technology accelerators.
10 videos |
34m
Assessment
Badge
SHOW MORE
FREE ACCESS
EARN A DIGITAL BADGE WHEN YOU COMPLETE THESE COURSES
Skillsoft is providing you the opportunity to earn a digital badge upon successful completion on some of our courses, which can be shared on any social network or business platform.
Digital badges are yours to keep, forever.BOOKS INCLUDED
Book
Big Data For DummiesProviding a plain-English explanation of what big data is (and isn't), this friendly guide discusses the technology and database options supporting it, analytics that help you get meaning from your data, how to manage it, and what it can do for your company.
5h 22m
By Alan Nugent, Fern Halper, Judith Hurwitz, Marcia Kaufman
Book
SQL on Big Data: Technology, Architecture, and InnovationConsolidating SQL and the big data landscape, this in-depth guide provides a comprehensive overview, at a technology and architecture level, of different SQL technologies on big data tools, products, and solutions.
2h 34m
By Sumit Pal
Book
Beginning Apache Pig: Big Data Processing Made EasyShowing you how to use Apache Pig to develop lightweight big data applications easily and quickly, this book shows you many optimization techniques and covers every context where Pig is used in big data analytics.
3h 21m
By Balaswamy Vaddeman
Book
Big Data, Better Learning? How Big Data Is Affecting Organizational LearningExamining the responses of 418 learning and development professionals in position of managers and above from varying sectors, sizes, and locations, this report explores challenges and other considerations that learning leaders must address if they are to knowledgeably and capably manage big learning data and apply the insights it has to offer today's organizational learning functions.
46m
By ASTD Research
Book
Big Data: Terms, Definitions and ApplicationsAuthored by EMC Proven Professionals, Knowledge Sharing articles present ideas, expertise, unique deployments, and best practices. This article discusses the various new structures of data, the three V's that form the basis of big data, and the new dimensions that have arisen as challenges while discussing the big data.
27m
By Anuj Mediratta
Book
Big Data Processing Beyond Hadoop and MapReduceAuthored by EMC Proven Professionals, Knowledge Sharing articles present ideas, expertise, unique deployments, and best practices. This article provides an overview of various new and upcoming alternatives to Hadoop MR.
23m
By Ravi Sharda
Book
Big Data Made Easy: A Working Guide to the Complete Hadoop ToolsetApproaching the problem of managing massive data sets from a systems perspective, this book explains the roles for each project (like architect and tester, for example) and shows how the Hadoop toolset can be used at each system stage - and then explains, in an easily understood manner and through numerous examples, how to use each tool.
5h 27m
By Michael Frampton
Book
Big Data: Storage, Sharing, and SecurityExamining Big Data management from an R&D perspective, this thorough resource covers the 3S designs-storage, sharing, and security-through detailed descriptions of Big Data concepts and implementations.
9h 21m
By Fei Hu
SHOW MORE
FREE ACCESS
BOOKS INCLUDED
Book
Taming The Big Data Tidal Wave: Finding Opportunities in Huge Data Streams with Advanced AnalyticsExploring a number of big data concepts and how they can be applied to improve your organization's analytics, this user-friendly handbook shows you step by step how to design, incorporate, and profit from a world-class advanced analytics ecosystem in today's big data environment.
5h 25m
By Bill Franks
BOOKS INCLUDED
Book
Big Data: Principles and Best Practices of Scalable Realtime Data SystemsThis book teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data.
4h 57m
By James Warren, Nathan Marz
Book
Big Data: A Very Short IntroductionDiscussing cases such as the Snowden affair, data security, and domestic smart devices which can be hijacked by hackers, this book explains how data is stored, analyzed, and exploited by a variety of bodies from big companies to organizations concerned with disease control.
2h 4m
By Dawn E. Holmes
BOOKS INCLUDED
Book
Big Data: A Very Short IntroductionDiscussing cases such as the Snowden affair, data security, and domestic smart devices which can be hijacked by hackers, this book explains how data is stored, analyzed, and exploited by a variety of bodies from big companies to organizations concerned with disease control.
2h 4m
By Dawn E. Holmes
Book
Principles and Practice of Big Data: Preparing, Sharing, and Analyzing Complex Information, Second EditionBringing a set of techniques and algorithms that are tailored to Big Data projects, this book offers case studies across a range of scientific and engineering disciplines and provides insights into semantics, identification, de-identification, vulnerabilities and regulatory/legal issues.
11h 16m
By Jules J. Berman
Book
Big Data For DummiesProviding a plain-English explanation of what big data is (and isn't), this friendly guide discusses the technology and database options supporting it, analytics that help you get meaning from your data, how to manage it, and what it can do for your company.
5h 22m
By Alan Nugent, Fern Halper, Judith Hurwitz, Marcia Kaufman
Book
Big Data: Storage, Sharing, and SecurityExamining Big Data management from an R&D perspective, this thorough resource covers the 3S designs-storage, sharing, and security-through detailed descriptions of Big Data concepts and implementations.
9h 21m
By Fei Hu
Book
Big Data ManagementFocusing on the analytic principles of business practice and big data, this book provides an interface between the main disciplines of engineering/technology and the organizational and administrative aspects of management.
4h 47m
By Benjamin Lev, Fausto Pedro García Márquez
Book
Big Data, Better Learning? How Big Data Is Affecting Organizational LearningExamining the responses of 418 learning and development professionals in position of managers and above from varying sectors, sizes, and locations, this report explores challenges and other considerations that learning leaders must address if they are to knowledgeably and capably manage big learning data and apply the insights it has to offer today's organizational learning functions.
46m
By ASTD Research
Book
Big Data: Understanding How Data Powers Big BusinessFull of practical techniques, real-world examples, and hands-on exercises, this book explores the technologies involved in Big Data, as well as how to find areas of the organization that can take full advantage of big data.
3h 36m
By Bill Schmarzo
Book
Data Ethics: Practical Strategies for Implementing Ethical Information Management and Governance, Second EditionLearn how organizational data can be governed according to ethical principles with this practical guide.
7h 7m
By Daragh O Brien, Katherine O'Keefe
SHOW MORE
FREE ACCESS
SKILL BENCHMARKS INCLUDED
Big Data
Big data represents high volume, high-velocity information assets, which enable better analytics, insight, decision making, and process automation. Big data is a field that treats ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software. Learn how big data can be analyzed for insights that lead to better decisions and strategic business moves. This benchmark evaluates your understanding of this topic. Being aware of potential knowledge gaps allows you to better understand your current competency and areas for improvement, so you can find suitable content and curate your own learning path. The courses recommended at the end of this benchmark can help you fill potential gaps in your knowledge.
7m
| 7 questions
Big Data Awareness (Entry Level)
The Big Data Awareness benchmark measures whether a learner has exposure to big data concepts, including what big data is, various sources of big data, formats, applications, and use cases for big data analytics. A learner who scores high on this benchmark demonstrates that they have the foundational knowledge of big data.
15m
| 15 questions
Big Data Literacy (Beginner Level)
The Big Data Literacy benchmark measures whether a learner has exposure to big data concepts like what big data is, various sources of big data, formats, applications, and use cases of big data analytics, distributed architecture for handling big data, various tools/technologies, and frameworks for carrying out big data analytics. A learner who scores high on this benchmark demonstrates that they have good knowledge to start learning and working on big data technologies with supervision and training.
22m
| 22 questions
Technology Essentials
The Technology Essentials benchmark will measure your ability to recall and relate the underlying concepts of digital technologies. You will be evaluated on your understanding of standard technologies; you will also be asked to recall common vocabulary from the tech industry and understand the importance of addressing legacy within complex systems. A learner who scores high on this benchmark demonstrates that they have the essential digital technology skills and can understand and grasp the underlying technical concepts and practices.
15m
| 10 questions
Data Lakes Competency (Intermediate Level)
The Data Lakes Competency (Intermediate Level) benchmark assesses your recognition of core data lake concepts. You will be evaluated on your skills in recognizing high-level elements of data lakes, architectures, and techniques. Learners who score high on this benchmark demonstrate that they have a solid understanding of intermediate-level data lake architecture techniques.
20m
| 15 questions
SHOW MORE
FREE ACCESS
