Month: June 2018

Key Stakeholders: Chief Sales Officer, Sales Directors and Managers, Sales Operations Directors and Managers, Training Officers, Learning and Development Professionals

Top Takeaways: If you want an efficient sales team you need to provide them with the right tools and train them effectively. If you want sales enablement and training tools that are highly effective they need to be grounded in learning science – the marriage of psychology and brain science. Many sales teams and sales focused vendors have access to these tools. What is needed is an effective way to leverage these tools to maximum advantage. This is where learning science comes in. In this report, I briefly outline the learning science behind sales enablement, people skills training and situational awareness.

(Note: This report represents the first step in an ongoing research initiative focused on critically evaluating the effectiveness of sales enablement and sales training solutions on the market. My goal in this research is to critically evaluate and accurately reflect the current state of the sales enablement and sales training sector from the perspective of learning science.)
Continue reading Optimizing Sales Enablement and Sales Training by Leveraging Learning Science: A Brief Primer

Key Stakeholders: IT managers, data scientists, data analysts, database administrators, application developers, enterprise statisticians, machine learning directors and managers, existing enterprise Cloudera customers

Why It Matters: As Cloudera continues its pivot towards becoming a full-service machine learning and analytics platform, its latest updates enhance its ability to retain existing customers of its commercial data lake and Hadoop distribution looking to expand into data science workflows, and attract net-new data science customers.

Top Takeaway: Cloudera’s additions to its Data Science Workbench provide a more rigorous, scientific approach to data science than prior versions, and allow for speedier implementation of results into enterprise software applications.

Cloudera’s announcements at Strata London in late May reflect the next steps in its transformation from a Hadoop distribution and commercial data lake into a full-service machine learning and analytics platform. Key to this transformation are two new capabilities in Cloudera Data Science Workbench: Experiments, which introduces versioning to DSW, and Models, which streamlines and standardizes the model deployment process. Both of these capabilities add rigor and reproducibility to the data science process.

To read the full report, please download it from our research library.

Two weeks ago (May 21, 2018), at Informatica World 2018, Informatica announced a new phase in its partnership with Microsoft. Slated for release in the second half of 2018, the two companies announced that Informatica’s Integration Platform as a Service, or IPaaS, would be available on Microsoft Azure as a native service. This is a different arrangement than Informatica has with other cloud vendors such as Google or Amazon AWS. In those cases, Informatica is more of an engineering partner, developing connectors for their on-premises and cloud offerings. Instead, Informatica IPaaS will be available from the Azure Portal and integrated with other Azure services, especially Azure SQL Server, Microsoft’s cloud database and Azure SQL Data Warehouse.
Continue reading Microsoft Azure Plus Informatica Equals Cloud Convenience