Providing the speed, scale, & centralised management you need to build an enterprise data platform
Datoop is a big data services driven startup that thrives in helping enterprises in their journey to become a leader in their respective domain. We understand the information driven nature of internet and the power of data.
At Datoop we do not make clients instead we make partners. We are experts in big data solutions and we work very closely with our partners to understand their requirements, and translate them into solutions. The company offers a business-to-business solution to enterprises.
Datoop is new but not our team; we boast an average experience of 9 years of our core technical team.
Datoop has created a new service category and we are proud to have the early entrant advantage in the Indian Big Data domain. We are masters in Big Data Science and experts in churning out information from any kind of data (structured/unstructured).
1 Week
- Architect a hadoop cluster -
Install or upgrade Big Data Suite on upto 100 nodes across one or two clusters.
Review existing hadoop cluster and related applications.
Recommend performance tuning, data compression and scheduler configuration.
Finalize the environment for successful implementation of Hadoop Cluster.
Document the recommended configuration for the Hadoop Cluster.
2 Weeks
- Customize Data Pipeline -
Identify solution requirements to include data sources, transformation and egress points.
Architect & develop pilot implementation for upto 3 data sources, file transformations & one target system.
Develop a deployment architecture that will result in a production deployment plan.
Review the hadoop cluster & application configuration.
Document the system recommendations.
2 Weeks
- Analyze with Hadoop System -
Review use case requirements & existing hardwares and recommend changes.
Design & develop a process for loading data from upto 2 data sources.
Design & implement a data storage, schema, and partitioning system.
Design & prototype a data integration process.
Design & implement specific data processing jobs and document the solution.
1 Week
- Authenticate and Authorize Access -
Review security requirements & provide an overview of data security policies.
Audit architecture & systems in light of security policies & best practices.
Install & integrate local MIT Kerberos KDC with active directory.
Review security integration for users & administrators.
Document administration & control features in applicable components.
4 Weeks
- Timeline from Conceptualization to Production -
Review cluster architecture, ingestion pipeline, schema & data partitioning system.
Review data jobs or analytic processes, & review data serving & result publishing systems.
Recommend performance tuning, data compression & scheduler configuration.
Document the configuration, review operation team's skills.
Review management and monitoring processes & production procedures.
PLAN
Identify your business goals and establish business requirements. Identify the right technology framework, architecture patterns, tools, product development life cycle.
IMPLEMENT
Identify your business goals and establish business requirements. Identify the right technology framework, architecture patterns, tools, product development life cycle.
MIGRATE
We will help you migrate existing content from legacy SQL databases and other sources into no-sql db while maintaining an archive copy.
PRODUCTION
Use cluster monitoring to view and optimize usage, memory patterns, and thread patterns. Implement best maintenance strategies for practices like decommissioning a node and load-balancing a cluster.
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