Tag: Excel

Feed: SAS Blogs. Author: Charlie Chase. Analytics-driven forecasting means more than measuring trend and seasonality. It includes all categories of methods (e.g. exponential smoothing, dynamic regression, ARIMA, ARIMA(X), unobserved component models, and more), including artificial intelligence, but not necessarily deep learning algorithms. That said, deep learning algorithms like neural networks can also be used for demand forecasting, depending on the situation.        When it comes to demand forecasting and planning these days, many people believe demand-driven and market-driven are interchangeable. There are some basic similarities - you need to forecast true demand, and use more advanced analytics to sense and ... Read More

Feed: IBM Big Data & Analytics Hub - All Content; Author: vinay-shukla; On June 13th 2017, Hortonworks and IBM announced an extension of our partnership. A key part of this partnership is the collaboration on IBM Data Science Experience (DSX). This collaboration is win-win in that it brings a production-ready full-cycle data science experience to Hortonworks Data Platform (HDP) customers and provides DSX customers access to information stored within HDP data lakes with an enterprise-grade compute grid. For most businesses, data is a key competitive differentiator. Increasingly, data science is employed to fully leverage this data. Data science remains a ... Read More

Feed: R-bloggers. Author: dtholmes@mail.ubc.ca. Background From time to time I have wanted to bring an online table into an R dataframe. While in principle, the data can be cut and paste into Excel, sometimes the table is very large and sometimes the columns get goofed up in the process. Fortunately, there are a number of R tools for accomplishing this. I am just going to show one approach using the rvest package. The rvest package also makes it possible to interact with forms on webpages to request specific material which can then be scraped. I think you will see the ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: David Sweenor. The development of Big Data, artificial intelligence and predictive analytics has created extravagant expectations for enterprise productivity growth — and aroused popular anxiety about intelligent information systems taking jobs from human workers. It is ironic, against that backdrop, that what is holding back widespread adoption of these technologies is, of all things, a manpower shortage. Big data and advanced analytics are the products of data science. What keeps companies from putting them to effective use is an acute shortage of data scientists. The US alone is facing a projected ... Read More

Feed: Planet big data. Author: Curt Monash. August 10, 2017 1. In June I wrote about burgeoning interest in data security. I’d now like to add: Even more than I previously thought, demand seems to be driven largely by issues of regulatory compliance. In an exception to that general rule, many enterprise have vague mandates for data encryption. In awkward contradiction to that general rule, there’s a general sense that it’s just security’s “turn” to be a differentiating feature, since various other “enterprise” needs are already being well-addressed. We can reconcile these anecdata pretty well if we postulate that: Enterprises generally ... Read More

Feed: Hortonworks Blog – Hortonworks. Author: Vinay Shukla. Author: Vinay Shukla, Hortonworks, Huzefa Hakim, IBM On June 13th, 2017, Hortonworks and IBM announced the extension of our partnership. A key part of this partnership is the collaboration on IBM’s Data Science Experience. This collaboration is win-win in that it brings a production-ready full cycle data science experience to HDP customers and provides DSX customers access to information stored within HDP data lakes with an enterprise grade compute grid. For most businesses, data is a key competitive differentiator. Increasingly, to fully leverage this data, Data Science is employed. Data Science remains ... Read More

Feed: SAS Blogs. Author: Anita Lakhotia. Where can you compare your skills with those of other experts, particularly data scientists? Or have the opportunity to program informally, just because it's fun? Hackathons. I talked to Fabian Buchert, himself a data scientist, about his experiences at the last Data4good Hackathon, on 6 May in Heidelberg on the SAS campus. How did you hear about this Data4Good Hackathon? Via the DataViz Meet-up, because the hackathon is organised by the DataViz community around Frankfurt am Main. I find Meet-ups are an excellent way to combine personal and business interests, because they have a ... Read More

Feed: Microsoft Azure Blog. Author: Ketan Ghelani. The Azure Log Analytics service is rolling out an upgrade to existing customers today – offering powerful search, smart analytics, and even deeper insights. This upgrade provides an interactive query language and an advanced analytics portal, powered by a highly scalable data store resembling Azure Application Insights. This creates a consistent monitoring experience for IT operations and developers. In the biggest upgrade since its launch, the new and improved Azure Log Analytics brings you a simple yet very powerful query language with all the capabilities requested in the language feedback. Over the last ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Vincent Granville. The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular. The online version of the book is now complete and will remain available online for free. Source for picture: click here Content Table of Contents Acknowledgements Notation 1 Introduction Part I: Applied Math and Machine Learning Basics2 Linear Algebra 3 Probability and Information Theory 4 Numerical Computation 5 Machine Learning Basics Part II: Modern Practical Deep Networks6 Deep Feedforward Networks 7 Regularization for Deep ... Read More

Feed: Planet big data. Author: Julie Steele. How CDOs can make an impact quickly  |  August 8th, 2017 Editor’s Note: In a recent post, Sanjay Mathur and Scott Kurth wrote that CDOs have 100 days to get the ball rolling downhill on digital transformation. CDOs know they need to move beyond the traditional focus of data governance and work to create new data products and value for the business, but there are some very real challenges to doing this efficiently. The following are some of the frequently asked questions we’ve received on this topic. 1. What are some techniques the ... Read More