Leverage Hadoop as your pilot project to gain organizational buy-in and build institutional learning.
Onsite Workshop
The lack of a defined and comprehensive approach to big data leads to:
Inability to address the skills gaps of database experts and data scientists
Inappropriately handling of single points of failure
Compliance and security risks due to the lack of security in many big data products
A well-defined big data tool stack provides the ability to:
Quickly handle large volumes of data with multiple schemas
Leverage the scalability of the database cluster to accommodate load spikes
Implement redundancies to ensure high availability and fault tolerance
Module 1: Assess fit for big data
The Purpose
Understand the current big data landscape.
Identify the project team.
Assess the current data analytics stack.
Key Benefits Achieved
Understand the organization’s readiness for big data development.
Activities:
Outputs:
1.1
Document and assess the development process
Data analytics stack
1.2
Assess the data analytics stack
Development process flow
1.3
Address the gaps in the stack
Big data project team
Module 2: Draw the big data flow
The Purpose
Map the requirements to big data.
Draw the big data flow.
Key Benefits Achieved
Ensure business requirements are mapped to each component of the big data flow.
Activities:
Outputs:
2.1
Document the business requirements and use cases
List business requirements
2.2
Draw the top-down and bottom-up big data flows
Big data flow target state
Module 3: Build the Hadoop stack
The Purpose
Choose the appropriate installation approach.
Import data into Hadoop.
Develop the MapReduce program.
Select big data analytics tools.
Conduct end-to-end testing.
Key Benefits Achieved
Create a baseline Hadoop stack that fits the organization’s needs.
Understand the challenges of installing and managing the Hadoop stack.
Activities:
Outputs:
3.1
Select the installation approach
Complete pilot Hadoop stack fitted for the organization
3.2
Classify the imported data
Test and validate points in the Hadoop stack
3.3
Select the data collection tools
3.4
Design the relational schema
3.5
Test and validate the dataflow
3.6
Choose analytics tools
3.7
Perform end-to-end testing
Module 4: Roll out Hadoop in the organization
The Purpose
Prepare the Hadoop stack for deployment.
Gain institutional learning.
Create an organizational rollout plan
Key Benefits Achieved
Activities:
Outputs:
4.1
Establish instrumentation points
Big data instrumentation points to measure value
4.2
Optimize the Hadoop stack
List of tools to improve performance of Hadoop
4.3
Develop an organization rollout plan
4.4
Establish a stakeholder communication plan
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Onsite Workshops offer an easy way to accelerate your project. If you are unable to do the project yourself, and a Guided Implementation isn’t enough, we offer low-cost onsite delivery of our Project Workshops. We take you through every phase of your project and ensure that you have a road map in place to complete your project successfully.
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