Big Data Bootcamp (Apache Hadoop/Pig/Hive)
-
The trainers give notes in very details.
← | →
-
The course and the team were very much appreciable. It was a great learning experience.
← | →
Short course
Inhouse
Description
-
Type
Short course
-
Level
Beginner
-
Methodology
Inhouse
-
Duration
2 Days
-
Start date
Different dates available
This big data training course will provide a technical overview of Apache Hadoop for project managers, business managers and data analysts. Students will understand the overall big data space, technologies involved and will get a detailed overview of Apache Hadoop.The course will expose students to real world use cases to comprehend the capabilities of Apache Hadoop. Students will also learn about YARN and HDFS and how to develop applications and analyze Big Data stored in Apache Hadoop using Apache Pig and Apache Hive. Each topic will provide hands on experience to the students.
Facilities
Location
Start date
Start date
About this course
Upon completion of this course, you will be able to:Learning Objectives:Learn about the big data ecosystemUnderstand the benefits and ROI you can get from your existing dataLearn about Hadoop and how it is transforming the workspaceLearn about MapReduce and Hadoop Distributed File systemLearn about using Hadoop to identify new business opportunitiesLearn about using Hadoop to improve data management processesLearn about using Hadoop to clarify resultsLearn about using Hadoop to expand your data sources Learn about scaling your current workflow to handle more users and lower your overall performance costLearn about the various technologies that comprise the Hadoop ecosystemLearn how to write a simple mapreduce job from Java or your favorite programming languageLearn how to use a very simple scripting language to transform your dataLearn how to use a SQL like declarative language to analyze large quantities of dataLearn how to connect your existing data warehouse to the Hadoop ecosystemLearn how to move your data to the Hadoop ecosystemLearn how to move the results of your data analysis to Business Intelligence Tools like TableauxLearn how to automate your workflow using oozie Learn about polyglot persistence and identifying the right tool for the right jobLearn about future trends in Big data and technologies to keep an eye onDiscover tips and tricks behind successful Hadoop deployments
Anybody who is involved with databases, data analysis, wondering how to deal with the mountains of data (anywhere gigabytes of user/log data etc to petabytes will benefit from this program).This course is perfect for:Business AnalystsSoftware EngineersProject ManagersData AnalystsBusiness CustomersTeam LeadersSystem Analysts
No prior knowledge of big data and/or Hadoop is required for this class. Some prior programming experience is a plus for this class, but not necessary.
Provides a concise introduction to Bid Data for Business Analysts
Reviews
-
The trainers give notes in very details.
← | →
-
The course and the team were very much appreciable. It was a great learning experience.
← | →
Course rating
Recommended
Centre rating
Edward S. Parker
Veronica Barnes
This centre's achievements
All courses are up to date
The average rating is higher than 3.7
More than 50 reviews in the last 12 months
This centre has featured on Emagister for 6 years
Subjects
- Data Mining
- Apache
- Systems
- Cloud
- Data Analytics
- Hadoop
- HIVE
- Pig
- Meta data
- Dirty Data
Teachers and trainers (1)
Bright Solutions
Trainer
Course programme
#text-block-10 { margin-bottom:0px; text-align:left; }
1. Introduction to Big Data
* Big Data – beyond the obvious trends
* Exponentially increasing data
* Big data sources
* Data warehousing, business intelligence, analytics, predictive statistics, data science
#text-block-11 { margin-bottom:0px; text-align:left; }
2. Survey of Big Data technologies
First generation systems
Second generation systems
Enterprise search
Visualizing and understanding data with processing
NOSQL databases
Apache Hadoop
#text-block-12 { margin-bottom:0px; text-align:left; }
3. Introduction to Hadoop:
What is Hadoop? Who are the major vendors?
A dive into the Hadoop Ecosystem
Benefits of using Hadoop
How to use Hadoop within your infrastructure?
#text-block-13 { margin-bottom:0px; text-align:left; }
4. Introduction to MapReduce
What is MapReduce?
Why do you need MapReduce?
Using Mapreduce with Java and Ruby
#text-block-14 { margin-bottom:0px; text-align:left; }
5.Introduction to Yarn
What is Yarn?
What are the advantages of using Yarn over classical MapReduce?
Using Yarn with Java and Ruby
#text-block-15 { margin-bottom:0px; text-align:left; }
5. Introduction to HDFS
What is HDFS?
Why do you need a distributed file system?
How is a distributed file system different from a traditional file system?
What is unique about HDFS when compared to other file systems?
HDFS and reliability?
Does it offer support for compressions, checksums and data integrity?
#text-block-16 { margin-bottom:0px; text-align:left; }
7. Data Transformation
Why do you need to transform data?
What is Pig?
Use cases for Pig
#text-block-17 { margin-bottom:0px; text-align:left; }
8. Structured Data Analysis?
How do you handle structured data with Hadoop?
What is Hive/HCatalog?
Use cases for Hive/HCatalog
Big Data Bootcamp (Apache Hadoop/Pig/Hive)