Greenplum Analytics Lab The Fastest Path to Analytical Insight
Greenplum Analytics Lab
EMC Greenplum Analytics Lab brings Greenplum’s Data Scientists to your site to help your team shorten the timeline to reach actionable analytical results. By combining services, training, and, in some cases, hardware and software, these unique labs bring the latest tools, methods, and technologies to bear on Big Data analytics challenges. Our team partners with your analysts, data platform administrators, and business leadership to solve your top business challenges and find new opportunities in your data, all on an accelerated schedule.
To help Greenplum UAP users get a head start in data science, we have built a team of experienced data scientists, many with PhD’s, who have experience in industry verticals. With expertise in achieving business objectives using analytic tools, the Greenplum Data Science team works with customers daily, advancing their projects and enabling them to make new discoveries from their big data. This team exists to help Greenplum users identify opportunities to extract business value from big data using advanced analytics while helping to grow the skills of your data science teams through coaching and on-site support.
Potential benefits of engaging Greenplum Data Scientists include:
- Shorten time to value for critical analytical challenges
- Identify new ways to extract value from your big data using analytics
- Deliver complex analytical models in weeks, not months
- Develop or refine your analytical roadmap quickly
- Advance skill development and preempt resource scarcities
- Develop pragmatic plans for embarking on your Big Data Analytics journey
- Benefit from the experiences of leading analytic practitioners
Our experts working with your team, on your data, delivering real business value
Rapid changes in analytical capabilities, swiftly evolving data sources, and ever-changing tools can impede progress in all but the most experienced teams. Let Greenplum and its team of experts help fill that gap. In as little as one day, Greenplum can help steer your organization down a path to agile Big Data Analytics.
Time is of the Essence
Greenplum UAP brings a platform of rich analytical capabilities to your data science teams, however their ability to capitalize upon it will depend on many factors. For those who seek optimum time-to-value and shortest ROI while building out analytics capabilities and roadmaps, Greenplum Analytical Lab is the answer.
Help is At the Ready
Greenplum Analytics Lab leverages Greenplum’s growing team of highly experienced data scientists – from leading analytics companies – to bear on your early analytics opportunities to assure early results and tractable roadmaps.
A Variety of Deliverables:
- Greenplum Analytics Labs are available according to a range of project scopes and deliverables including:
- Analytics Lab Primer: A one-day workshop, to deliver a roadmap to achieving insight using Big Data Analytics.
- Analytics Lab 100: A two-week project, that provides you with Quick Insight along with training on analytics methods and tools delivered by a Greenplum Data Scientist.
- Analytics Lab 600: A longer, 6-week engagement that begins with development of a high-level roadmap, followed by data quality assessment, analysis of analytical insights gleaned from the data study, ready-do-deploy analytical model and the training and documentation to support future use.
- Analytics Lab 1200: Extensive 12-week engagement expanding the scope of the Analytics Lab 600 to address challenges of larger scope that could be completed in a Lab 600, targeting additional detail and modeling complexity.
In addition to the Analytics Labs described above, Greenplum also provides custom Analytics Lab engagements when doing so better suits the need of the client.
Bring Greenplum Data Scientists to your site to help your team shorten the timeline to reach actionable analytical results. By combining services, training, and in some cases, hardware and software, these unique labs bring the latest tools, methods and technologies to bear on big data analytics challenges.
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