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Introduction to Big Data Training
Nivå: Foundation
Snittbetyg:
4,51/5 Based on 134 Reviews
Lär dig att använda analysverktyg och tekniker inom Big Data som hjälper er att ta bättre affärsbeslut genom denna introduktionskurs till Big Data. Under utbildningen får du lära dig sätt att lagra data som möjliggör effektiv bearbetning och analys, Du får kunskaperna du behöver för att lagra, hantera, bearbeta och analysera stora mängder ostrukturerade data för att skapa en lämplig data lake.
NEW! DATA SCIENCE BUNDLES NOW AVAILABLE
This course is now available as part of a multi-course, blended learning premium training bundle for a limited time! Take your Data Science skills and career to the next level with multi-modal learning path bundles that lead to certification.
Nyckelfunktioner:
- Choose from blended on-demand and instructor-led learning options
- Learn Big Data Analytics
- After-course instructor coaching benefit
- Learning Tree end-of-course exam included
- After-course computing sandbox included
Du kommer lära dig att:
- Lagra, bearbeta och analysera ostrukturerade data
- Välja rätt sätt att lagra Big Data för skilda datauppsättningar
- Använda Hadoop för att bearbeta och få insikter från stora datamängder
- Ställa frågor till stora datauppsättningar med Pig och Hive
- Planera och implementera en Big Data-strategi i er verksamhet
Välj den utbildningsform som passar dig bäst
BLANDAT LÄRANDE
On-demand och online lärarträffar
Unlimited annual access to:
- 2 on-demand courses
- 5 eBooks
- 1-day instructor-led training course
LIVE, LÄRARLEDD
I klass & Live, Online-utbildning
- 3-day instructor-led training course
- One-on-one after-course instructor coaching
- After-course computing sandbox
PREMIUM UTBILDNING
Klassrum, On-demand och självstudier
Unlimited annual access to:
- 2 on-demand courses
- 5 eBooks
- 1-day instructor-led training course
- 3-day instructor-led training course
- One-on-one after-course instructor coaching
- Learning Tree end-of-course exam included
- After-course computing sandbox included
FÖRETAGSINTERN UTBILDNING
Teamträning
- Bring this or any training to your organization
- Full - scale program development
- Delivered when, where, and how you want it
- Blended learning models
- Tailored content
- Expert team coaching
Anpassa kurs och innehåll efter teamets behov
Kontakta ossUtveckla dig och ditt team med anpassade eller öppna kurser alternativt e-learning
Learning Tree erbjuder kundanpassad utbildning hos er, öppna kurser i Stockholm, London eller Washington, möjlighet att delta via våra Anywhere centers (Malmö, Göteborg, Linköping, Stockholm eller Borlänge) eller olika former av e-learning med lärarstöd. Läs mer på www.learningtree.se/priser .
On-demand och online lärarträffar
Big Data Blended utbildningsinformation
This product offers access to 2 on-demand courses and 5 eBooks that have been mapped directly to the objectives of the 3-day course. At any time during your annual access to this offering, you may attend one of our 1-day course events focused specifically on Big Data Insights, Technologies & Trends (4500).
Utbildningsplan On-Demand
-
On-Demand Courses
- Mastering Big Data Analytics with PySpark
- Master Big Data Ingestion and Analytics with Flume, Sqoop, Hive and Spark
-
eBooks
- Artificial Intelligence for Big Data
- Big Data Architect's Handbook
- Modern Big Data Processing with Hadoop
- Big Data Processing with Apache Spark
- Practical Big Data Analytics
Introduction to Big Data FAQs
-
What background do I need for this Introduction to Big Data?
Working knowledge of the Microsoft Windows platform and basic database concepts.
Typical job roles include: Project and IT Managers, Database Administrators & Data Architects, Developers & SQL Developers, Data Scientists & Business Intelligence.
-
Where does Big Data fit in my data science training?
Data science is about obtaining insights from data using methods from several disciplines like statistics, linear algebra, differential equations, machine learning, etc. Many of the activities in data science involve large amounts of data, especially for training models. Some will use data that cannot be efficiently stored in a relational fashion; unstructured data. Often data needs to be processed and conclusions reached extremely quickly. These requirements for large volume, variety and velocity create an overlap between big data, how to store, secure, manage and access the data, and data science, how best to utilise the data in order to draw conclusions and gain insights from it.
-
Is the on-demand content the same as the 3-day instructor class?
No. While the content selected does map to the objectives of the instructor-led course, it does not include a recorded version of the instructor-led class. The objectives have been re-imagined to be presented in digital, self-guided formats. -
What on-demand content will I receive?
An outline of the content you will receive can be seen above. You will also get access to any new on-demand content that becomes available during your annual enrolment period. -
Does this include any practical, hands-on learning?
Yes! Each book and video begins with a step by step guide for you to set up a coding environment on your personal computer. The course content is full of examples and practical advice, followed up by the chance to embed your learning through real world tasks. All example code is available to download, copy and use - giving you the chance to work and practise as you read and watch. -
How will I access my course materials if I choose this method?
Once payment is received, you will receive an email from Learning Tree with all the links and information you need to get started. -
How can I sign up for a review session of this Introduction to Big Data?
Once you are enrolled in the program, specific details and dates will be sent to you.
Instructor-Led Training
You'll be able to register for an Instructor-Led Training Session at any time after you've placed your order.
-
25 jan
(1 dag)
10:00 - 5:30 CCET Online (AnyWare) -
4 apr
(1 dag)
11:00 - 6:30 CCST Online (AnyWare) -
27 jun
(1 dag)
11:00 - 6:30 CCST Online (AnyWare) -
20 sep
(1 dag)
11:00 - 6:30 CCST Online (AnyWare)
I klass & Live, Online-utbildning
Note: This course runs for 3 dagar
-
30 mar - 1 apr 9:00 - 16:30 CEST Stockholm / Online (AnyWare)
Boka Din Kursplats -
15 - 17 feb 9:00 - 16:30 GMT Online (AnyWare)
Boka Din Kursplats -
3 - 5 maj 9:00 - 16:30 BST Online (AnyWare)
Boka Din Kursplats -
19 - 21 jul 9:00 - 16:30 BST Online (AnyWare)
Boka Din Kursplats -
9 - 11 feb 15:00 - 22:30 CCET New York / Online (AnyWare)
Boka Din Kursplats -
20 - 22 apr 15:00 - 22:30 CCST Herndon, VA / Online (AnyWare)
Boka Din Kursplats -
27 - 29 jul 15:00 - 22:30 CCST New York / Online (AnyWare)
Boka Din Kursplats
Kurs med startgaranti
När du ser symbolen för “Guaranteed to Run” vid ett kurstillfälle vet du att kursen blir av. Garanterat.Important Intro to Big Data Lärarledd kursinformation
Big Data Training Course Description
In this hands-on Introduction to Big Data Course, learn to leverage big data analysis tools and techniques to foster better business decision-making – before you get into specific products like Hadoop training (just to name one). Learn ways of storing data that allow for efficient processing and analysis, and gain the skills you need to store, manage, process, and analyse massive amounts of unstructured data to create an appropriate data lake.
View this Big Data training course as part of a learning path defined by job roles ›
Recommended Experience
- Working knowledge of the Microsoft Windows platform and basic database concepts
Who Should Attend
- Anyone needing to implement, enhance your big data environment and looking to advance their analytics career by ensuring foundational knowledge
- Typical job roles include: Project Managers and IT Managers, Database Administrators & Data Architects, Developers & SQL Developers, Data Scientists & Business Intelligence
All-Inclusive: After-Course Coaching for Real-World Application
Learning Tree is with you from the beginning of your planning until you return to your job ready to apply your new skills – with instructor coaching to answer real-world big data implementation challenges.Take Your Big Data Course Online or In-person:
Schedules are busy, but big data training online makes it easy to level-up your career. If you need Big Data online training, we’ve got you covered. Our AnyWare course delivery option gives you the advantages of a live classroom right from the comfort of your computer screen – no matter where you are.
Into to Big Data Lärarledd Utbildningsplan
-
Introduction to Big Data
Defining Big Data
- The four dimensions of Big Data: volume, velocity, variety, veracity
- Introducing the Storage, MapReduce and Query Stack
Delivering business benefit from Big Data
- Establishing the business importance of Big Data
- Addressing the challenge of extracting useful data
- Integrating Big Data with traditional data
-
Storing Big Data
Analysing your data characteristics
- Selecting data sources for analysis
- Eliminating redundant data
- Establishing the role of NoSQL
Overview of Big Data stores
- Data models: key value, graph, document, column–family
- Hadoop Distributed File System
- HBase
- Hive
- Cassandra
- Amazon S3
- BigTable
- DynamoDB
- MongoDB
- Redis
- Riak
- Neo4J
Selecting Big Data stores
- Choosing the correct data stores based on your data characteristics
- Moving code to data
- Messaging with Kafka
- Implementing polyglot data store solutions
- Aligning business goals to the appropriate data store
-
Processing Big Data
Integrating disparate data stores
- Mapping data to the programming framework
- Connecting and extracting data from storage
- Transforming data for processing
- Subdividing data in preparation for Hadoop MapReduce
Employing Hadoop MapReduce
- Creating the components of Hadoop
- MapReduce jobs
- Executing Hadoop
- MapReduce jobs
- Monitoring the progress of job flows
The building blocks of Hadoop MapReduce
- Distinguishing Hadoop daemons
- Investigating the Hadoop Distributed File System
- Selecting appropriate execution modes: local, pseudo–distributed and fully distributed
- Accelerating process with Spark
Handling streaming data
- Comparing real–time processing modelsLeveraging Storm to extract live events
- Leveraging Spark Streaming to extract live events
- Combining streaming and batch processing in a Lambda architecture
-
Tools and Techniques to Analyse Big Data
Abstracting Hadoop MapReduce jobs with Pig
- Communicating with Hadoop in Pig Latin
- Executing commands using the Grunt Shell
- Streamlining high–level processing
Performing ad hoc Big Data querying with Hive
- Persisting metadata in the Hive Metastore
- Performing queries with HiveQL
- Investigating Hive file formats
Creating business value from extracted data
- Visualising processed results with reporting tools
- Querying in real time with Impala
-
Developing a Big Data Strategy
Defining a Big Data strategy for your organisation
- Establishing your Big Data needs
- Meeting business goals with timely data
- Evaluating commercial Big Data tools
- Managing organisational expectations
Enabling analytic innovation
- Focusing on business importance
- Framing the problem
- Selecting the correct tools
- Achieving timely results
-
Implementing a Big Data Solution
- Selecting suitable vendors and hosting options
- Balancing costs against business value
- Keeping ahead of the curve
Introduction to Big Data FAQs
-
What is big data?
Big data is a term used to define data sets that have the potential to rapidly grow so large that they become unmanageable. The Big Data movement includes new tools and ways of storing information that allow efficient processing and analysis for informed business decision-making. -
What is the difference between big data and machine learning?
Big data refers to the data set that has huge, and growing, volume that can quickly become unwieldy. Machine learning is a subsection of Artificial Intelligence (AI) that can help you extract value from big data to solve problems. -
How does big data help businesses?
Understanding how to work with big data can help you glean useful insights from large amounts of data, which can help you and your organisation make better business decisions. -
Where does Big Data fit in my data science training?
Data science is about obtaining insights from data using methods from several disciplines like statistics, linear algebra, differential equations, machine learning, etc. Many of the activities in data science involve large amounts of data, especially for training models. Some will use data that cannot be efficiently stored in a relational fashion; unstructured data. Often data needs to be processed and conclusions reached extremely quickly. These requirements for large volume, variety and velocity create an overlap between big data, how to store, secure, manage and access the data, and data science, how best to utilise the data in order to draw conclusions and gain insights from it.
-
Does Learning Tree offer this Introduction to Big data online?
Schedules are busy, but big data training online makes it easy to level-up your career. If you need Big Data online training, we’ve got you covered. Our AnyWare course delivery option gives you the advantages of a live classroom right from the comfort of your computer screen – no matter where you are.
Klassrum, On-demand och självstudier
Note: This course runs for 3 dagar
-
30 mar - 1 apr 9:00 - 16:30 CEST Stockholm / Online (AnyWare)
-
15 - 17 feb 9:00 - 16:30 GMT Online (AnyWare)
-
3 - 5 maj 9:00 - 16:30 BST Online (AnyWare)
-
19 - 21 jul 9:00 - 16:30 BST Online (AnyWare)
-
9 - 11 feb 15:00 - 22:30 CCET New York / Online (AnyWare)
-
20 - 22 apr 15:00 - 22:30 CCST Herndon, VA / Online (AnyWare)
-
27 - 29 jul 15:00 - 22:30 CCST New York / Online (AnyWare)
Kurs med startgaranti
När du ser symbolen för “Guaranteed to Run” vid ett kurstillfälle vet du att kursen blir av. Garanterat.Big Data Obegränsad åtkomst kursinformation
-
Course Description
This product offers access to 2 on-demand courses and 5 eBooks that have been mapped directly to the objectives of the 3-day course. At any time during your annual access to this offering, you may attend one of our 1-day course events focused specifically on Big Data Insights, Technologies & Trends (4500). Enrolling in this bundle also grants you access to any of our multi-day Introduction to Big Data (1250) course events.
-
How to Schedule Your Instructor-Led Training
Once payment is received, you will receive details for your Unlimited Access Training Bundle via email. At that time, you may call or email our customer service team for assistance in enrolling in the event date of your choice.
Utbildningsplan On-Demand
-
On-Demand Courses
- Mastering Big Data Analytics with PySpark
- Master Big Data Ingestion and Analytics with Flume, Sqoop, Hive and Spark
-
eBooks
- Artificial Intelligence for Big Data
- Big Data Architect's Handbook
- Modern Big Data Processing with Hadoop
- Big Data Processing with Apache Spark
- Practical Big Data Analytics
Big Data Training FAQs
-
What background do I need for this Introduction to Big Data?
Working knowledge of the Microsoft Windows platform and basic database concepts.
Typical job roles include: Project and IT Managers, Database Administrators & Data Architects, Developers & SQL Developers, Data Scientists & Business Intelligence.
-
Where does Big Data fit in my data science training?
Data science is about obtaining insights from data using methods from several disciplines like statistics, linear algebra, differential equations, machine learning, etc. Many of the activities in data science involve large amounts of data, especially for training models. Some will use data that cannot be efficiently stored in a relational fashion; unstructured data. Often data needs to be processed and conclusions reached extremely quickly. These requirements for large volume, variety and velocity create an overlap between big data, how to store, secure, manage and access the data, and data science, how best to utilise the data in order to draw conclusions and gain insights from it.
-
Is the on-demand content the same as the 3-day instructor class?
No. While the content selected does map to the objectives of the instructor-led course, it does not include a recorded version of the instructor-led class. The objectives have been re-imagined to be presented in digital, self-guided formats. -
What on-demand content will I receive?
An outline of the content you will receive can be seen above. You will also get access to any new on-demand content that becomes available during your annual enrolment period. -
Does this include any practical, hands-on learning?
Yes! Each book and video begins with a step by step guide for you to set up a coding environment on your personal computer. The course content is full of examples and practical advice, followed up by the chance to embed your learning through real world tasks. All example code is available to download, copy and use - giving you the chance to work and practise as you read and watch. -
How will I access my course materials if I choose this method?
Once payment is received, you will receive an email from Learning Tree with all the links and information you need to get started. -
How can I sign up for a review session of this Introduction to Big Data?
Once you are enrolled in the program, specific details and dates will be sent to you. -
How do I schedule my instructor-led training?
Once payment is received, you will receive details for your Unlimited Access Training Bundle via email. At that time, you may call or email our customer service team for assistance in enrolling in the event date of your choice.
Instructor-Led Training
You'll be able to register for an Instructor-Led Training Session at any time after you've placed your order.
-
25 jan
(1 dag)
10:00 - 5:30 CCET Online (AnyWare) -
4 apr
(1 dag)
11:00 - 6:30 CCST Online (AnyWare) -
27 jun
(1 dag)
11:00 - 6:30 CCST Online (AnyWare) -
20 sep
(1 dag)
11:00 - 6:30 CCST Online (AnyWare)
Teamträning
Data Science
Bundled Training
Extend learning beyond a single event with bundled content designed for real-world application.
Har du frågor om vilken utbildning som är rätt för dig?
08-506 668 00
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It allows us to direct your request to the appropriate Customer Care team.
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