Towards a Data-driven Organization: A Roadmap for Analytics

@machinelearnbot

I was one of those fortunate few to have an opportunity to work on both sides of the table, both as a provider of services and as a consumer of technology and business services. A few years back when I was working on the other side of the table, I have been asked to explore setting-up an analytics lab to support decision makers in different BUs and Functions. I went through the first few preparatory steps of taking stock of BI-DW practices across the locations, data availability, and data quality, key analytics requirements as per existing practices. Next, I attempted the ever-difficult task of talking to some of the stake-holders on what they expect from an Analytics Lab. When asked about the time they spend on creating a report vs. analyzing a report; one of the more vocal feedback was: "Reports are usually made because we are asked to submit them for reviews.


Data Analytics and Machine Learning: Driving Speed to Insight

#artificialintelligence

No question about it: Data-driven organizations are clearly on to something. Such organizations are three times more likely to report significant improvement in decision making, according to a PwC Global Data & Analytics survey, which polled 1,135 executives. Research by MIT's Center for Digital Business uncovered similar results in interviews with executives at 330 North American businesses. "The more companies characterized themselves as data-driven, the better they performed on objective measures of financial and operational results," MIT's Andrew McAfee and Erik Brynjolfsson reported in Harvard Business Review. So what do analytics leaders--and their data-driven initiatives--need to succeed?


LP--Data-Driven Strategies About Life & Work Data-Driven Marketing Strategy

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Discover the power of data and how it can transform your business. Many of the leading high-growth startups use data-driven strategies. Join me and learn how your business can benefit from those same approaches!


Business Metrics for Data-Driven Companies Coursera

@machinelearnbot

This Coursera Specialization: Excel to MySQL: Analytic Techniques for Business, is about how'Big Data' interacts with business, and how to use data analytics to create value for businesses. This specialization consists of four courses and a final Capstone Project, where you will apply your skills to real-world business process. You will learn to perform sophisticated data-analysis functions using powerful software tools such as Microsoft Excel, Tableau, and MySQL. To learn more, watch the video and review the specialization overview document we provided. In the first course of the specialization: Business Metrics for Data-Driven Companies, you will be able to learn best practices for using data analytics to make any company more competitive and more profitable; learn to recognize the most critical business metrics and distinguish those from mere data; understand the vital but different roles business analysts, business data analysts, and data scientists each play in various types of companies; and know exactly the skills required to be hired for, and succeed at, these high-demand jobs.


Towards a Data-driven Organization: A Roadmap for Analytics

@machinelearnbot

Building a Data-driven Organization requires identifying and prioritizing the opportunities where advanced analytics can make a material difference to the quality of decisions! I was one of those fortunate few to have an opportunity to work on both sides of the table, both as a provider of services and as a consumer of technology and business services. A few years back when I was working on the other side of the table, I have been asked to explore setting-up an analytics lab to support decision makers in different BUs and Functions. I went through the first few preparatory steps of taking stock of BI-DW practices across the locations, data availability, and data quality, key analytics requirements as per existing practices. Next, I attempted the ever-difficult task of talking to some of the stake-holders on what they expect from an Analytics Lab.