Mon-Fri 9am to 6pm CST
Learn by Example: HBase - The Hadoop Database
Taught by a team comprising 2 ex-Flipkart Lead Analysts, ex-Googlers and 2 Stanford-educated.
Self-Paced
Learning Style
Course
Learning Style
Intermediate
Difficulty
5 Hours
Course Duration
Course Info
Certificate
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9:00 AM - 5:00 PM CST
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Taught by a team comprising 2 ex-Flipkart Lead Analysts, ex-Googlers and 2 Stanford-educated.
Course Information
About the course:
Taught by a team comprising 2 ex-Flipkart Lead Analysts, ex-Googlers and 2 Stanford-educated. This team has decades of experience in the field working on big data analysis jobs.
Relational DB is so old and stuffy! Welcome to the HBase-A New Age database solution.
HBase: Do you believe your relational DB no longer gives you the versatility that you need? Column based storage, low latency, and no set schema make HBase a great option for your app's user-definable needs.
Course Objective:
· CRUD in and with the Java API, MapReduce, Counters, Filters
· 25 Examples resolved to address all facets of data operating in HBase
Use HBase to implement your own Social Network notification service
HBase and its position in the Hadoop ecosystem, HBase design and what separates HBase from RDBMS as well as other Hadoop technologies such as Hive.
Audience:
· Engineers interested in switching away from RDBMS and using HBase for their DB solution
· Everyone involved in learning HBase, NoSQL and the centralized control of databases
· People who use Hadoop ecosystem methods for analytical analysis and want OLAP and OLT to have one unified framework
Prerequisite:
· You will need a bit of Java programming experience
· You'll require an IDE to execute Java code, Eclipse and Intellij IDEA are both strong choices
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Outline
More Information
| Subjects | Big Data |
|---|---|
| Lab Access | No |
| Technology | Hadoop |
| Learning Style | Self-Paced Learning |
| Learning Type | Course |
| Difficulty | Intermediate |
| Course Duration | 5 Hours |
| Language | English |
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Course Expert:
Tom Robertson
(Data Science Enthusiast)
Tom is an innovator first, and then a Data Scientist & Software Architect. He has integrated expertise in business, product, technology and management. Tom has been involved in creating category defining new products in AI and big data for different industries, which generated more than hundred million revenue cumulatively, and served more than 10 million users.
As a Data Scientist and Software Architect Tom has extensive experience in data science, engineering, architecture and software development. To date Tom has accumulated over a decade of experience in R, Python & Linux Shell programming.
Tom has expertise on Python, SQL, and Spark. He has worked on several libraries including but not limited to Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn, SciPy, NLTK, Keras, and Tensorflow.
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