Hadoop Online & Classroom Training in Hyderabad India

Hadoop online training in India

HADOOP / BIG DATA :

Hadoop is an open-source software framework for storing and processing big data in a distributed fashion on large clusters of commodity hardware.
All the modules in Hadoop are framed with a basic presumption
 that hardware failures (of machines) are common and thus should be automatically handled in software by the framework.

Best Hadoop Online training institute

Hadoop/ Big Data training Has become one of the most talked about technologies.
Hadoop has developed to overcome issues of legacy storage and processing architectures such as relational databases.

What does Hadoop solve?
• Institutions are observing that important predictions can be made by sorting through and analyzing Big Data.
• However, since 80% of this data is “unstructured”, it must be formatted (or structured) in a way that makes it suitable for data mining and subsequent analysis.
• Hadoop is the mainstage for designing Big Data, and solves the problem of making it useful for analytics purposes.
• Divides The data across multiple machines arranged into a Hadoop Cluster , rather than storing your Big Data on one centralized database management system.

What is Hadoop Cluster ?
• A Hadoop cluster consists of commodity servers specifically designed for storing and altering Big Data, and each runs Hadoop individually. These machines process the data parallel in only one network.
• Single Hadoop cluster can be made up of multiple machines, each with two, four, or eight CPUs – thus contributing to Hadoop’s fast processing speed.
• The Hadoop distributed file system (HDFS) is a distributed, scalable, and portable file-system written in Java for the Hadoop framework.
• Each node in a Hadoop has a single NameNode; along with a group of Data Nodes they form the HDFS cluster.

What are the benefits of a Hadoop cluster structure?
• Expandable : If the current nodes in a Hadoop cluster are overwhelmed with data, it is possible to easily add others to expand processing capacity.
• Efficient: Hadoop clusters enable enormous size of data to be framed and sorted for analytic purposes with high throughput and low latency.



Why to choose Hadoop?
• Low cost : The open-source framework is free and uses commodity hardware to store large quantities of data.

• Computing power : Its distributed computing model can quickly process very large volumes of data. With increasing computing nodes , the processing power also increases.


• Scalability :By addition of more nodes , you can easily grow your system.  Only some administration is required.

• Storage flexibility :There is no need to preprocess data before saving it ,like the traditional relational databases . The unstructured data includes  text, images and videos. Bulk quantity of data can be stored as you want and decide how to use it later.

• Inherent data protection and self-healing capabilities : Data and application processing are protected against hardware failure. If one node drops , jobs are automatically redirected to other nodes to make sure the distributed computing does not breakdown. And it automatically stores multiple copies of all data.
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Hadoop training in hyderabad

Big Data Hadoop Online Training in Hyderabad

Hadoop & Big Data - Cloudera

Before we go running off looking to solve an issue, let us first make sure people actually possess an issue that must be solved. Believe back to that particular IT supervisor training in the event that you and I were planning today to make a database you may or might not have received, how would we go about carrying it out?

Let us say that we wished to develop a database. The best approach to consider a database is always to imagine a table. This table has columns and rows. In 's' address database, we will make a fresh row to hold your address info by making a brand new column and we'll start out.

That is it! Now we've got a database that is tiny: it includes one record (yours) and that record holds 6 bits of data: your address as well as your name. Now if 's went one step farther and added the names and addresses of everyone who lives to the database in your town it could grow to include thousands of records, maybe even numerous records determined by your geographical area.

Hadoop online training in Hyderabad

Now imagine which you possessed a flower shop. One day you find that you've got a lot of roses. You don't need to send this e-mail to everyone since when they live too far away they will not make the drive to your shop and you had only be wasting the money to send the letter to them.

After the database supplies this particular list to you, it is possible to go sell your roses and address each of your letters.

The other types of data which is not going to fit into both of these groupings are called as Unstructured Information. Data from social networking websites, web logs are unable to be saved analysed and processed in databases, it is therefore categorised as Unstructured Information to list a couple.

Based on NASSCOM, Ordered Data accounts for 10% of the complete data which exists now in the world wide web. Generally, organizations use of Structured and Semi Structured Data using information analytics tools that are conventional evaluation. There clearly was no advanced programs accessible till the Map Reduce framework which was designed by Google to analyse the Unstructured Data.

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Hadoop training hyderabad

Hadoop Training in Hyderabad

Hadoop Training in Hyderabad :

Bigdata Hadoop training Hyderabad

The Apache (registered company) Hadoop project is a framework enabling distributed processing of large data sets via a network of computers using straightforward programming models. It's born to scale servers that are single up each that can offer storage and local computation.

The training course finish know how and performance of the framework and is subject to various features of Hadoop. To begin with one is going to be introduced as basic outline in regards to the tools and functionalities, history etc., its usages, to Hadoop Framework All kinds of doubts relating to why Hadoop is required, what are its benefits or advantages over the previous framework will undoubtedly be cleared to produce a robust foundation for the class.

It will be compares with file systems that are conventional that are accessible. Once we're finished with all design and the elements of the framework we move on to another level of learning in the training.

In the following degree one gets to learn about its overview the Hadoop Disperse File System, design and compatibility. Here the Hadoop Training in Hyderabad bunch reconciliation may be learnt and recoveries as a result of component failures are understood

Planning of capability and cluster on which it could work will probably be taught once reconciliation methods and the recovery methods are understood. The entire setup of hardware and software is preserved here. Network is finalized at the same time.

Another period after preparation is installation. There are supply alternatives and various deployment kinds for different type of scheduling and information access Online Hadoop Training in Hyderabad. One learns about the most important part that the administrator must always know this is the installation of Hadoop.

One has to work with Hadoop following the deployment is done. This aids in numerous ways to access the file system which was created earlier.

Another major tool of Hadoop framework is Map Reduce engine. All of the process and terminologies associated will soon be learnt at this level. One will be able after comprehension how successful is this tool to work.

After a framework that is whole installed and is setup, the bunch needs to be configured.

The gist of the course lies in administration and upkeep of the Hadoop framework. One learns about the name node as well as the data node. The admin work of removing and adding nodes is an important part only at that amount.

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Hadoop training in hyderabad

BigData Hadoop Training in Hyderabad

Map Reduce in BigData Hadoop

MapReduce has existed for quite a while, but until and unless the underlying theories which forms the base of MapReduce are understood, an individual will be unable to learn more about range and the real possibility which MapReduce seeks to offer.

Among the main aspects of ensuring that you simply learn Hadoop in a holistic way would be to comprehend the essential theories which form the foundation of the modern world occurrence. Just once these theories have already been well understood, you can move ahead to comprehend the specific dynamics itself.

The facet of MapReduce continues to be present for quite a while and continues to be executed in a variety of scenarios in organizations all over the world, but, the real possibility of the applications is unable to be used until the specific dynamics as well as the theories which form the essential of the applications are well comprehended. Therefore, by preventing to jump in the execution facet of MapReduce, of imparting knowledge related to helping individuals learn Hadoop training in Hyderabad  our political orientation is distinct, yet surprisingly high consequence giving at the same time.

Yet, in addition to the comprehension the theories there are several other facets which playan important part in comprehending the dynamics. The problem statement is included by among the facets. 

All the features are well considered and efficiently produced in Hadoop's batch training. We ensure that Hadoop's dynamics are described in in-depth, to this kind of holistic amount the users can make great usage of the info and begin efficiently in handling the big data set easily, using the notions of MapReduce. Learn Hadoop and comprehend diversification, extent and the real possibility that MapReduce provides for you.

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Hadoop training in hyderabad

Hadoop Big Data Online Training

Hadoop Online Training in Hyderabad:

Hadoop is a wonderful and very demanding technology in this worldwide.  ALL companies and organizations are moving to  Hadoop why because it is free where mean open source.  In bigdata many tools and technologies is there but compare all modules hadoop is best modules.  Rstrainings Providing hadoop training in Hyderabad and online through world wide.This is best training center in this world. Many hadoop trained candidates placed in different companies through worldwide. Mainly training's providing country wise USA, Japan,China, India, Australia,Turkey, Italy etc.Many companies are using many databases but Hadoop is  one of the framework .The many companies of the world using this database depending on using of data and volume of the history of the data. The main components in the Big data many tools is there all tools have their own capability of the working capacity. Many guys from other countries.

Hadoop online training

Hadoop is a biggest and grow thing future. Every one like small sectors to big sectors business depends . Present now a trend using Big data with cloud. This is new trend for the generation. The mail sector of the company wise .
Three years back ihis is not booming in this world but now trend is every business moving to Hadoop.
By using cloud components we are creating and storing data bites to terabytes with secured and safe zone. Every one learning training and taking corporate training from different centers and organization but this is hot crack in technology wise. our training centers are giving with quality training with caring of each classes after every classes they are giving some examples and some real time scenarios.Carrier wise we can select center for our better future.
They are giving some guidance for carrier step and market analyse and we will be get good worth of the knowledge from rstraining center. bigdata components are changing depending on market demands every day we are getting different changes link some other tools adding and some new technology updated versions are adding in that ...
The main components in bigdata is hive,pig ,zookeeper, hbase and mapreduce.. and etc
In this Hadoop we are using java concepts in mapreduce concepts , java mean only core java we are using in map reducing concepts.tools wise world wide have many many tools and technologies is there but all are have some their won capability and working capacity. In India many people was learning hadoop for growing of technologies many it and business magnates are announced in future all industries are depending on hadoop why because this is open source and there is no huge of costs. And employment also increase in future recruitment wise also all companies will take many candidates from different different countries.In all countries governments also encouraging of technology. The many industries in this world hotel,it , constructions,steel,retail , travel, manufacturing etc all sectors have huge of data volume.In that time we have many databases is there like informatica, sql server,and sap data basis.In that movement these all databases is very constable why because this databases are maintainable from third party and cost wise also very hight to compare hadoop so that finally we can give good points hadoop. Very fast processing and maintenance speed also very good.
The apache company announcing this big data. In first stage of this not understandable for every one . Day by day population also growing and human mindset also changed thinking wise and creating wise. Every one thinking  about hadoop . Finally every one got some good information from hadoop frame work.
Why because these companies are selecting cloud servers for maintenance and security problems solving.
In job market wise In India and usa very demanding on Hadoop In USA present job market wise billing rate is starting from 60 usd.
every one talk about hadoop training and hadoop jobs in future.Some don’t know  and they are consulting many training center and service centers.
In this we are getting many knowledge from training center.They have good setup and good knowledgeable persons, All trainers are working in top mnc company and they have many years of experience in real-time sectors

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hadoop training

Hadoop Training

       RS TRAINING'S is an outstanding ONLINE IT TRAINING and CLASSROOM IT TRAINING institute with State of Art infrastructure led by the finest trainers in the market. We offer Online training to the learners in all parts of the world with the implementation of modern technologies like Gotomeeting and WebEx and we provide online training,class room training and corporate training. 

      Online Training is simple; Join anywhere, learn from your own place,connect to the internet, decide your own pace and become a technical expert on specific domain.

Features:

• Live interactive sessions.
• Preeminent Training quality.
• Accessible in all geographical locations.
• Saves your valuable time and money for your journey.

    Our Corporate IT Training service is a blend of ingenious customization and implementation of modules from our trainers to improve the efficiency of the company outputs. 

We provide corporate Training in different ways:

• Onsite Training: The employees will get trained while performing their job roles. This type of training will be supervised by experienced trainers.


• Institution Training: This training is mainly focused on developing the skill levels of the employees.


• External Learning: This kind of knowledge imparting takes place through seminars or short courses or through online training outside the companies.

   classroom training         

                  The domain experts will provide highest level of training in the specific domain with real time scenarios. Their experience will be evident during their training sessions. Students will have the extra benefit of getting good exposure to the tips on domain expertise through the interactions with our trainers. The students will be provided with practice labs equipped with high configuration computers.

We build the resumes of our students and provide placement assistance to them through our corporate clients.

• Instructor led training with proper training facilities.
• Free demo session to have a look and feel of our training quality.
• Friendly environment for gathering the domain specific knowledge.
• Reasonable fee structure.
• Practice lab under expert supervision.
• Soft copies and Hard copies of the Material for the benefit of students.

Register for Classroom IT training with Rs trainings to make a successful IT career with bright future

Hadoop

Course Objective Summary

During this course, you will learn:

• Introduction to Big Data and Analytics
• Introduction to Hadoop
• Hadoop ecosystem - Concepts
• Hadoop Map-reduce concepts and features
• Developing the map-reduce Applications
• Pig concepts
• Hive concepts
• Sqoop concepts
• Flume Concepts
• Oozie workflow concepts
• Impala Concepts
• Hue Concepts
• HBASE Concepts
• ZooKeeper Concepts
• Real Life Use Cases

Reporting Tool

• Tableau 

1. Virtualbox/VM Ware

• Basics
• Installations
• Backups
• Snapshots

2. Linux

• Basics
• Installations
• Commands

3. Hadoop 

• Why Hadoop?
• Scaling
• Distributed Framework
• Hadoop v/s RDBMS
• Brief history of hadoop

4. Setup hadoop 

• Pseudo mode
• Cluster mode
• Ipv6
• Ssh
• Installation of java, hadoop
• Configurations of hadoop
• Hadoop Processes ( NN, SNN, JT, DN, TT)
• Temporary directory
• UI
• Common errors when running hadoop cluster, solutions

5. HDFS- Hadoop distributed File System

• HDFS Design and Architecture
• HDFS Concepts
• Interacting HDFS using command line
• Interacting HDFS using Java APIs
• Dataflow
• Blocks
• Replica

6. Hadoop Processes

• Name node
• Secondary name node
• Job tracker
• Task tracker
• Data node

7. Map Reduce

• Developing Map Reduce Application
• Phases in Map Reduce Framework
• Map Reduce Input and Output Formats
• Advanced Concepts
• Sample Applications
• Combiner

8. Joining datasets in Mapreduce jobs

• Map-side join
• Reduce-Side join

9. Map reduce – customization

• Custom Input format class
• Hash Partitioner
• Custom Partitioner
• Sorting techniques
• Custom Output format class

10. Hadoop Programming Languages :-

I.HIVE

• Introduction
• Installation and Configuration
• Interacting HDFS using HIVE
• Map Reduce Programs through HIVE
• HIVE Commands
• Loading, Filtering, Grouping….
• Data types, Operators…..
• Joins, Groups….
• Sample programs in HIVE

II. PIG 

• Basics
• Installation and Configurations
• Commands….

OVERVIEW HADOOP DEVELOPER

11. Introduction

12. The Motivation for Hadoop

• Problems with traditional large-scale systems
• Requirements for a new approach

13. Hadoop: Basic Concepts

• An Overview of Hadoop
• The Hadoop Distributed File System
• Hands-On Exercise
• How MapReduce Works
• Hands-On Exercise
• Anatomy of a Hadoop Cluster
• Other Hadoop Ecosystem Components

14. Writing a MapReduce Program

• The MapReduce Flow
• Examining a Sample MapReduce Program
• Basic MapReduce API Concepts
• The Driver Code
• The Mapper
• The Reducer
• Hadoop’s Streaming API
• Using Eclipse for Rapid Development
• Hands-on exercise
• The New MapReduce API

15. Common MapReduce Algorithms

• Sorting and Searching
• Indexing
• Machine Learning With Mahout
• Term Frequency – Inverse Document Frequency
• Word Co-Occurrence
• Hands-On Exercise.

16.PIG Concepts..

• Data loading in PIG.
• Data Extraction in PIG.
• Data Transformation in PIG.
• Hands on exercise on PIG.

17. Hive Concepts.

• Hive Query Language.
• Alter and Delete in Hive.
• Partition in Hive.
• Indexing.
• Joins in Hive.Unions in hive.
• Industry specific configuration of hive parameters.
• Authentication & Authorization.
• Statistics with Hive.
• Archiving in Hive.
• Hands-on exercise

18. Working with Sqoop

• Introduction.
• Import Data.
• Export Data.
• Sqoop Syntaxs.
• Databases connection.
• Hands-on exercise

19. Working with Flume

• Introduction.
• Configuration and Setup.
• Flume Sink with example.
• Channel.
• Flume Source with example.
• Complex flume architecture.

20. OOZIE Concepts
21. IMPALA Concepts
22. HUE Concepts
23. HBASE Concepts
24. ZooKeeper concepts

Reporting Tool..

Tableau

This course is designed for the beginner to intermediate-level Tableau user. It is for anyone who works with data – regardless of technical or analytical background. This course is designed to help you understand the important concepts and techniques used in Tableau to move from simple to complex visualizations and learn how to combine them in interactive dashboards.

Course Topics

Overview

• What is visual analysis?
• Strengths/weakness of the visual system.

Laying the Groundwork for Visual Analysis

• Analytical Process
• Preparing for analysis

Getting, Cleaning and Classifying Your Data

• Cleaning, formatting and reshaping.
• Using additional data to support your analysis.
• Data classification

Visual Mapping Techniques

• Visual Variables : Basic Units of Data Visualization
• Working with Color
• Marks in action: Common chart types

Solving Real-World Problems with Visual Analysis

• Getting a Feel for the Data- Exploratory Analysis.
• Making comparisons
• Looking at (co-)Relationships.
• Checking progress.
• Spatial Relationships.
• Try, try again.

Communicating Your Findings

• Fine-tuning for more effective visualization
• Storytelling and guided analytics
• Dashboards

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hadoop training

Hadoop online training in hyderabad

                       Hadoop is an open source software project that enables the distributed processing of large data sets across clusters of commodity servers. It is designed to scale up from a single server to thousands of machines, with a very high degree of fault tolerance. Rather than relying on high-end hardware, the resiliency of these clusters comes from the software’s ability to detect and handle failures at the application layer.

      Hadoop is supplemented by an ecosystem of Apache projects, such as Pig, Hive and Zookeeper, that extend the value of Hadoop and improves its usability.

Hadoop enables a computing solution that is:

Scalable– New nodes can be added as needed, and added without needing to change data formats, how data is loaded, how jobs are written, or the applications on top.

.Cost effective– Hadoop brings massively parallel computing to commodity servers. The result is a sizeable decrease in the cost per terabyte of storage, which in turn makes it affordable to model all your data

Flexible– Hadoop is schema-less, and can absorb any type of data, structured or not, from any number of sources. Data from multiple sources can be joined and aggregated in arbitrary ways enabling deeper analyses than any one system can provide

Fault tolerant– When you lose a node, the system redirects work to another location of the data and continues processing without missing a fright beat.

Rs Training's : is a brand and providing quality online and offline training's for students in world wide. Rs Training's providing Best Hadoop online training in Hyderabad.

RS TRAINING'S: Interactive training from Technological mavens to groom learners into technological aces.

RS TRAINING'S is an outstanding ONLINE IT TRAINING and CLASSROOM IT TRAINING institute with State of Art infrastructure led by the finest trainers in the market. We offer Online training to the learners in all parts of the world with the implementation of modern technologies like Gotomeeting and Web Ex.

    Our trainers are Domain experts with a proven experience of at least a decade in the real time environment. We believe in the policy that “Learning is the virtue of success in life”.The flexible course curriculum designed at RS TRAINING'S will be up to date in the technological race and be able to cater the requirement of both fresher’s and Professionals. Be it Corporate training or Online Training or Classroom Training for Hadoop ,RS TRAINING'S is elite and provides accomplished training services to cater the client needs.

Course Content:

Course Objective Summary

During this course, you will learn:

• Introduction to Big Data and Analytics
• Introduction to Hadoop
• Hadoop ecosystem - Concepts
• Hadoop Map-reduce concepts and features
• Developing the map-reduce Applications
• Pig concepts
• Hive concepts
• Sqoop concepts
• Flume Concepts
• Oozie workflow concepts
• Impala Concepts
• Hue Concepts
• HBASE Concepts
• ZooKeeper Concepts
• Real Life Use Cases

Reporting Tool

• Tableau 

1. Virtualbox/VM Ware

• Basics
• Installations
• Backups
• Snapshots

2. Linux

• Basics
• Installations
• Commands

3. Hadoop 

• Why Hadoop?
• Scaling
• Distributed Framework
• Hadoop v/s RDBMS
• Brief history of hadoop

4. Setup hadoop 

• Pseudo mode
• Cluster mode
• Ipv6
• Ssh
• Installation of java, hadoop
• Configurations of hadoop
• Hadoop Processes ( NN, SNN, JT, DN, TT)
• Temporary directory
• UI
• Common errors when running hadoop cluster, solutions

5. HDFS- Hadoop distributed File System

• HDFS Design and Architecture
• HDFS Concepts
• Interacting HDFS using command line
• Interacting HDFS using Java APIs
• Dataflow
• Blocks
• Replica

6. Hadoop Processes

• Name node
• Secondary name node
• Job tracker
• Task tracker
• Data node

7. Map Reduce

• Developing Map Reduce Application
• Phases in Map Reduce Framework
• Map Reduce Input and Output Formats
• Advanced Concepts
• Sample Applications
• Combiner

8. Joining datasets in Mapreduce jobs

• Map-side join
• Reduce-Side join

9. Map reduce – customization

• Custom Input format class
• Hash Partitioner
• Custom Partitioner
• Sorting techniques
• Custom Output format class

10. Hadoop Programming Languages :-

I.HIVE

• Introduction
• Installation and Configuration
• Interacting HDFS using HIVE
• Map Reduce Programs through HIVE
• HIVE Commands
• Loading, Filtering, Grouping….
• Data types, Operators…..
• Joins, Groups….
• Sample programs in HIVE

II. PIG 

• Basics
• Installation and Configurations
• Commands….

OVERVIEW HADOOP DEVELOPER

11. Introduction

12. The Motivation for Hadoop

• Problems with traditional large-scale systems
• Requirements for a new approach

13. Hadoop: Basic Concepts

• An Overview of Hadoop
• The Hadoop Distributed File System
• Hands-On Exercise
• How MapReduce Works
• Hands-On Exercise
• Anatomy of a Hadoop Cluster
• Other Hadoop Ecosystem Components

14. Writing a MapReduce Program

• The MapReduce Flow
• Examining a Sample MapReduce Program
• Basic MapReduce API Concepts
• The Driver Code
• The Mapper
• The Reducer
• Hadoop’s Streaming API
• Using Eclipse for Rapid Development
• Hands-on exercise
• The New MapReduce API

15. Common MapReduce Algorithms

• Sorting and Searching
• Indexing
• Machine Learning With Mahout
• Term Frequency – Inverse Document Frequency
• Word Co-Occurrence
• Hands-On Exercise.

16.PIG Concepts..

• Data loading in PIG.
• Data Extraction in PIG.
• Data Transformation in PIG.
• Hands on exercise on PIG.

17. Hive Concepts.

• Hive Query Language.
• Alter and Delete in Hive.
• Partition in Hive.
• Indexing.
• Joins in Hive.Unions in hive.
• Industry specific configuration of hive parameters.
• Authentication & Authorization.
• Statistics with Hive.
• Archiving in Hive.
• Hands-on exercise

18. Working with Sqoop

• Introduction.
• Import Data.
• Export Data.
• Sqoop Syntaxs.
• Databases connection.
• Hands-on exercise

19. Working with Flume

• Introduction.
• Configuration and Setup.
• Flume Sink with example.
• Channel.
• Flume Source with example.
• Complex flume architecture.

20. OOZIE Concepts
21. IMPALA Concepts
22. HUE Concepts
23. HBASE Concepts
24. ZooKeeper concepts

Reporting Tool..

Tableau

This course is designed for the beginner to intermediate-level Tableau user. It is for anyone who works with data – regardless of technical or analytical background. This course is designed to help you understand the important concepts and techniques used in Tableau to move from simple to complex visualizations and learn how to combine them in interactive dashboards.

Course Topics

Overview

• What is visual analysis?
• Strengths/weakness of the visual system.

Laying the Groundwork for Visual Analysis

• Analytical Process
• Preparing for analysis

Getting, Cleaning and Classifying Your Data

• Cleaning, formatting and reshaping.
• Using additional data to support your analysis.
• Data classification

Visual Mapping Techniques

• Visual Variables : Basic Units of Data Visualization
• Working with Color
• Marks in action: Common chart types

Solving Real-World Problems with Visual Analysis

• Getting a Feel for the Data- Exploratory Analysis.
• Making comparisons
• Looking at (co-)Relationships.
• Checking progress.
• Spatial Relationships.
• Try, try again.

Communicating Your Findings

• Fine-tuning for more effective visualization
• Storytelling and guided analytics
• Dashboards