Big Data Warehouse
Unstructured or Semi-Structure data from diverse sources such as weblogs, social media, email, customer service notes and a host of other sources have created pressures on the traditional relational EDW. How the EDW must change to embrace the intersection and value of unstructured data is the focus of our services in this category.
[accordions collapsible=true][accordion title=”Exploring the Possibilities for Big Data Analytics”]
Gavroshe has a proven methodology for helping clients capture, understand, and profile the concrete business opportunities that drive the need for, and are enabled through, big data analytics. This is a critical foundation for scoping and focusing efforts to deliver a successful proof of concept or pilot Big Data Analytics Solutions that will ensure success with production scale-out.
Our process begins by understanding the opportunities that have been identified by the business to date, capturing those opportunities into our proven Use Case Documentation Template, categorizing and profiling each use case across a number of important dimensions necessary to enable an ìapples to applesî evaluation of:
- Return On Investment
- Feasibility of Delivery
- Technology Alternatives
- Risk
This engagement can typically be delivered in an 8-week time-box and is enabled by the application of our proven Joint Requirements Planning process. Joint Requirements Planning is a proven and award winning workshop-based facilitation methodology that achieves significantly greater clarity, alignment and buy-in to decisions that are made over any other facilitation method (see description inside).[/accordion][accordion title=”Planning and Prototyping for Big Data Analytics”]
This engagement is typically delivered in a 90-day time-box and focuses on delivering a working proof of concept (POC) solution leveraging the targeted big data analytics technologies for the highest priority use case(s) identified by the business. The POC can be cloud-based or internally deployed and typically leverage technologies such as Hadoop, Map Reduce, HP Vertica, R, SAS, or other Big Data Analytic platforms such as Cassandra or MongoDB.
Elements of this engagement include:
- Guidance for technology acquisition, installation/configuration
- Hands-on technical support for data acquisition, integration, and analytics
- Capture of insights gained from POC to help guide production deployment and scale-up[/accordion][accordion title=”Production Build”]
We offer a variety of technical skills necessary to accelerate production deployment of the identified solution. These engagements are custom-configured and follow the proven Spiral Methodology approach to ensure incremental delivery of results aligned with business priorities and needs.[/accordion][/accordions]
