Big Data Strategy

Our Big Data Experts and Management Team works closely with your Organization to not just deliver our solutions but also to help you ascertain quality, commitment and the best means to utilize our services for your situation to achieve the ROI.

Big Data Strategy

We work with your Business and technology teams over ~4 weeks period to understand your Business drivers for leveraging Big Data, Organization’s readiness and then create a strategy and execution plan to capitalise on your data and analytics ambitions.

Key Outcomes

Big Data Strategy

  • Creation of a common understanding and definition
  • Near term objectives & strategy
  • Identification and prioritisation of key use cases

Big Data Readiness Assessment

  • Business Insights and Analytics that can be derived
  • People & Resources
  • Hardware, Software, Infrastructure
  • Data capture, processing, storage and sharing

Pilot Plans For Select Use Cases

  • Business benefits
  • Recommended Architectures
  • Execution plan

Hadoop Implementation

Hadoop saves cost but at the same time comes with some overhead. Given its architecture and limited skills available in the market, it is complex to plan, deploy, and manage a Hadoop implementation. Businesses trying to implement Hadoop face a complicated installation, other challenges and they’re tripped up by poor documentation, limited support and expert advise. For reasons like these, many organizations—even those with a detailed design in hand—fail to make the leap from Hadoop pilot to production.

Our experts have the right answer and provide a comprehensive service to help your organization master the challenges of implementing your selected distribution of Hadoop on your own hardware. Working from your Hadoop design, we’ll handle all phases of the project.

Key Outcomes

  • Assessment of your current situation including ROI
  • Planning and delivery of your implementation
  • Upgrade path
  • Actual installation, testing and Validation

We’ll ensure your Hadoop environment is tightly aligned with your business requirements. You can engage us for the implementation alone, or add support as part of a larger package.

Multi Temperature Data Management

Data in a Data Warehouse can be classified according to its temperature. The temperature of data is based on how old it is, how often it is accessed, how volatile it is, and how important the performance should be to access that data. Using faster, more expensive, storage for hot data and slower, less expensive, storage for cold data optimizes performance while helping to reduce overall cost. As part of this service our experts will provide guidelines and enable the key outcomes below.

Key Outcomes

  • Identify and characterize data into temperature tiers
  • Design the Architecture to accommodate multiple data temperatures
  • Provide easy means to move data from one temperature tier to another
  • Allocate more resources for hot data than to requests for cold data
  • Backup and recovery strategy for multiple data temperature tiers