• SpringML’s Data Integration for Wave Analytics

    April 25, 2017 | Author Girish Reddy

    The term “data integration” for most customers means complex projects that involve countless hours spent on extracting, transforming and joining data. In this post I’d like to draw a distinction between two types of integrations. Integration between transactional systems Integration from various systems to an analytics engine The first type… [Read More.]

  • Unbiased Sales Forecasting using Machine Learning

    April 14, 2017 | Author Girish Reddy

    Sales forecasting is a common task performed by sales organizations. Accurate forecasts allow organizations to make informed business decisions. It gives insight into how a company should manage its resources - people, time and cash. Companies derive forecasts based on historical sales, market conditions, competitive analysis and gut instinct. However… [Read More.]

  • Man vs Machine Forecasting Duel

    April 5, 2017 | Author Girish Reddy

    Sales forecasting is a common yet critical task performed by all sales organizations.  Though the process of forecasting tends to be complex it is straightforward to determine its accuracy.  One simply has to wait until the end of a forecasting period (e.g. end of quarter) and then compare forecasts with… [Read More.]

  • Customers who bought this item also bought – Salesforce Analytics

    April 3, 2017 | Author Andrew Shelton

    When analyzing consumer data, we instinctively segment customers and accounts using their purchase history. Historic sales data allows us to easily find customers that have purchased Product A and label them as Product A owners. The challenge has been handling instances where customers purchase Products A and B. If the… [Read More.]

  • Our take on Google Next Conference

    March 15, 2017 | Author Prabhu Palanisamy

    Google has been providing effective services for so long that we don’t remember how we lived without them. For me, no Google search or Gmail is as good as no power. But Google isn’t resting on its laurels. One of Google’s newest platforms – Google Cloud – is poised to… [Read More.]

  • Four reasons why Google Cloud ML is a compelling machine learning platform

    March 9, 2017 | Author Girish Reddy

    At SpringML we solve complex customer problems using Google Cloud Platform and Cloud ML.  Our solutions include real-time predictions, large scale video processing and transcription to name a few.  In this blog we highlight a few reasons why CloudML and TensorFlow provides a compelling machine learning platform. Distributed, high performance:… [Read More.]

  • SAQL step is the new values table.

    March 1, 2017 | Author Ram Palanki

    For those that migrated from legacy dashboards to new designer would have faced the scrolling issue of values table. In the new wave designer values table does not allow scrolling. In order to fix the issue we need to update the values table to new Step called saql step (More details here)… [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.]

  • How we design Machine Learning Models

    February 2, 2017 | Author Prabhu Palanisamy

    One of my favorite questions I ask customers on the topic of machine learning is to list out the top 3 words that come to their mind on Forecasting vs Predictive. Here are the most common answers Forecasting: Business need, Discipline and Math based. Predictive: No logic, black box and… [Read More.]