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Big data has gone mainstream. It reaches well beyond the initial group of Silicon Valley “new economy” tech companies and the new media companies that helped launch the industry. The big data adoption landscape has expanded to include automakers, big finance, big insurance companies, telecommunications, healthcare companies and big retailers. Big data is past the hype phase and adoption is accelerating, but success is not a given and challenges remain.
This informative technical general session is full of the “need to know” for anyone involved in an enterprise data landscape. Learn from experienced enterprise information strategists with real project experience about the path that big data is on, the obstacles along the path, and how to confidently join the big data revolution. Learn the players in the technology landscape and the ideal workloads for big data in enterprises. Learn where big data adds value to an existing enterprise information strategy and how to get the projects started and dropping the “not in production” label.
This 3.5-hour online course addresses the technical community as well as
the user community, providing guidance on how to penetrate and benefit
the enterprise. This practical session will help you make the most of
big data and make the best choices to ensure information remains an
unparalleled corporate asset.
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You will learn:
- A workable definition of big data so you know it when you see it
- Drivers for big data
- Big data in the enterprise
- The Hadoop framework for analytical big data
- NoSQL and operational big data
- An overall information architecture with big data
This course is geared towards:
- Business and Data Analysts
- BI Architects and BI Developers
- Data Architects
- Data Integrators
- Analytics Developers and Consumers
- Anyone who needs to understand the business and technical implications of Big Data
Module 0. About the Course (8 mins)
Module 1. Big Data Definition (34 mins)
- Big Data Introduction
- Big Data Technology
- Enablers for Big Data
Module 2. Big Data Drivers (28 mins)
- Big Data Drivers (28 mins)
- Value Density of Data
- Before Data was Big…
- Once Big Data Grew, Value was Realized
- Data is too Valuable to Discard
- Data is too Valuable to Ignore
- Focus Before Big Data
- Focus After Big Data
- Performance/Workload Optimization
- Cost of Storage
- Other Cost Drivers
- Analytic Need
- Implication for IT Skills
Module 3. Big Data in the Enterprise (21 mins)
- The Great Database Thaw
- Data Access in the Modern Enterprise
- Marz’s Lambda Architecture
- Row vs. Columnar Stores
- In-Memory
- Big Data & Analytics
- Leveraging Hadoop for Analytics
Module 4. Hadoop Ecosystem (40 mins)
- Hadoop Overview
- Hadoop Distributions
- Hadoop Framework
Module 5. NoSQL (31 mins)
- NoSQL “Schemaless” Data Modeling
- NoSQL Heartburn
- Key-Value Stores
- Document Oriented Database
- Graph Oriented Database
- Stream Processing Engines
- NewSQL
Module 6. Enterprise Architecture with Big Data (45 mins)
- Modern Components of Information Architecture
- ETL with Big Data Systems
- Analytic Patterns with Hadoop
- Where Do We go from Here?
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Click
–here- to download a more detailed outline of this course.
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This exam tests knowledge and understanding of basic concepts, principles, and terminology of big data.
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You will be tested in these areas:
- Big Data definition and concepts
- Big Data technologies
- Big Data cost, value, and use cases
- Big Data architecture
- Hadoop and MapReduce
- Hadoop Framework and components
- NoSQL concepts and databases
- NewSQL concepts and databases
- Enterprise architecture and big data
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Additional Information
Number of Questions: 20
Time Limit: 40 Minutes
Passing Score: 70%
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Once you pass the exam, you will receive a Certificate of Education documenting that you have demonstrated mastery of the topic. Further, the exam counts towards
Certified Information Management Professional (CIMP) designation in the Information Management Foundations, and Business Intelligence & Analytics tracks.
We recommend that you take detailed notes and review the course material multiple times before taking this exam.
Click here to learn more about CIMP exams.
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Course Review 
