CATEGORY: analytics

  • Using Informatica for Complex Data Integrations into Salesforce Einstein Analytics

    October 9, 2017 | Author Robert Anderson

    Salesforce Einstein Analytics is a great tool for end users to gain insights on business performance. However, critical business data doesn’t always live 100% within Salesforce. For example, manually maintained sales goals, commission plans, and revenue are external datasets that are often needed to get the full picture on business… [Read More.]

  • Where Classic Reports and Dashboards Fall Short

    September 29, 2017 | Author Nicolai Johnson

    One of the questions we get asked most often is why should I invest in Einstein Analytics? Everyone has built standard reports and dashboards, and they wonder what Einstein Analytics can do that classic Reports and Dashboards can’t. Since Einstein Analytics requires separate licenses, customers need to know they will… [Read More.]

  • Einstein Analytics – Sankey Chart Review

    September 24, 2017 | Author Andrew Shelton

    For those that work with Einstein Analytics and historic pipeline data, the upcoming Sankey chart is an exciting addition to the chart types suite. The purpose of the Sankey chart is to visualize how values flow from one dimension to another where the width of the flow line is proportional… [Read More.]

  • 4 Ways To Transform Your Wave Event Monitoring Application

    May 4, 2017 | Author Dan Thenguyen

    From Truck to Lamborghini Wave’s Event Monitoring (EM) app provides 15 pre-built dashboards that help bridge the gap between raw event data and visualization. Like a truck, it can handle great exertions of power and haul large items, but ultimately lacks the detail and proficiency of a Lamborghini. In this… [Read More.]

  • Five Best Practices for the Wave Dataflow

    February 20, 2017 | Author Matt Wittlief

    Once you have moved past creating the first handful of Datasets you need for your Dashboards in Wave, you might begin to notice that your Dataflow takes longer to run.  When working with our customers, we have found long and complex Dataflows that take over an hour to run which… [Read More.]

  • Machine Learning is Easy, then what is difficult?

    February 13, 2017 | Author Prabhu Palanisamy

    In the whole Machine Learning development, model development is the easy and least time-consuming effort. Operationalization is the hardest and that's where all projects are either failing or struggling to justify investment. It's not a one time effort. Most Machine Learning projects start with access to existing data and particular use case… [Read More.]

  • Spring ’17 – Salesforce Analytics

    January 9, 2017 | Author Prabhu Palanisamy

    We are excited about the upcoming Spring '17 release of Salesforce Analytics. As expected the whole platform upgrade is packed with new features and Salesforce Analytics is no exception. In this blog we cover some of the exciting features that avoids custom coding. Multi-metric Timeline chart This is a common… [Read More.]

  • How Customers and Partners will drive next industrial revolution

    December 23, 2016 | Author Prabhu Palanisamy

    In most companies, analytics is primarily inward. Companies have built their companies relying on in-house data analysis. Most of external communication is primitive, primarily email. But analytics doesn’t have to be solely internal. Instead, insights can — and should — be shared with an ecosystem of partners, helping everyone interact,… [Read More.]

  • Why Sales Ops Will Drive AI in Enterprises

    December 15, 2016 | Author Prabhu Palanisamy

    You already know how much of an impact a sales leader and his operations team can have on a business’s results. But perhaps it’s less obvious the impact these critical players can have on driving artificial intelligence (AI) development -- which will no doubt become an important factor for getting… [Read More.]

  • Supercharge Your Wave Investment (Part 2)

    November 4, 2016 | Author Prabhu Palanisamy

    Treat Wave as a Playbook for Winning In Part 1 of this blog series, I suggested you think of data as food to get more return from your Wave investment. In Part 2, I want you to think of your users as sports players and Wave as your playbook for… [Read More.]