access to data to help enterprises make better decisions. It can provide information of various “Information Assets” in an organization and how they interact with each other. These assets include Customer Databases, SCM Information, Personnel data, Manufacturing, Sales & Marketing Activity. Applications of BI: BI can be applied to MARCKM * Measurement - performance metrics, benchmarking etc., * Analytics - data mining, process mining, predictive modeling * Reporting - Data visualization
Words: 1444 - Pages: 6
INTRODUCTION TO BIG DATA IN RETAIL Big Data is a massive pool of data (both structured and unstructured) that cannot be processed using traditional database and software techniques. When any particular organization uses this catch phrase they refer to the technology that can be used to channelize this huge pool of data into some useful information. This channelization includes modification, creation, manipulation, storage, transfer, sharing and analysis of the data. Big data in Retail Consider
Words: 1664 - Pages: 7
White Paper Big Data Analytics Extract, Transform, and Load Big Data with Apache Hadoop* ABSTRACT Over the last few years, organizations across public and private sectors have made a strategic decision to turn big data into competitive advantage. The challenge of extracting value from big data is similar in many ways to the age-old problem of distilling business intelligence from transactional data. At the heart of this challenge is the process used to extract data from multiple sources
Words: 6174 - Pages: 25
------------------------------------------------- BIG Data February 8, 2015 Srinivas gogineni SAI SRAVAN KOLUKULA February 8, 2015 Srinivas gogineni SAI SRAVAN KOLUKULA Introduction Big data burst upon the scene in the first decade of the 21st century. The first organizations to embrace it were online and startup firms. Firms like Google, eBay, LinkedIn, and Facebook were built around big data from the beginning. Like many new information technologies, big data can bring about dramatic cost reductions
Words: 4913 - Pages: 20
Importing Data into Excel Image copyright Gina Sanders 2010. Used under license from Shutterstock.com © Cengage Learning. All rights reserved. No distribution allowed without express authorization. 17 FINDING INFORMATION WITH DATA MINING T he types of data analysis we discuss in this and other chapters of this book are crucial to the success of most companies in today’s datadriven business world. However, the sheer volume of available data often defies traditional methods of data analysis
Words: 23665 - Pages: 95
federal inspection of Centralia Mine. ( U.S. Mine Rescue Association, 2012) Perez and Scalan reports of the Centralia mine were very similar. ( U.S. Mine Rescue Association, 2012) That same year, Scanlan told Prudent which was the director of state mining board that he had to shut
Words: 1717 - Pages: 7
Disruptive Innovation: A new era of Crowdsourced Data Analytics! Abstract: The existing business paradigm of data analytics is set for a transformation. Today, companies are experimenting to replicate the “Outsourced data analytics” model to “Crowdsourced data analytics”. Companies like Kaggle, Crowdanalytix and others are hitting the headlines of top analytics blogs across the globe. The reason is that the new business model promises a drastic decrease in the cost of analytics for companies long
Words: 1574 - Pages: 7
Big Data Big Data and Business Strategy Businesses have come a long way in the way that information is being given to management, from comparing quarter sales all the way down to view how customers interact with the business. With so many new technology’s and new systems emerging, it has now become faster and easier to get any type of information, instead of using, for example, your sales processing system that might not get all the information that a manger might need. This is where big data
Words: 1883 - Pages: 8
lignite is the youngest variety of all coals, forming in the early to middle Miocene age about 15Ma. Several coal seams are formed and join up in the center of the Rhenish basin to form one main seam which reaches a maximum thickness of about 100m. Mining operations are carried out by RWE Power, one of Germanys biggest power producers and extraction of energy materials with an about 30% share in electricity generation is no. 1 in Germany and no. 3 in Europe with a 9% share. Lignite extraction by RWE
Words: 4896 - Pages: 20
White Paper Analysis of Large-Scale Bitcoin Mining Operations (or how Bitcoin miners make $845 Million a Year) Introduction of the Modular 1.2MW Bitcoin Mining Container For inexpensive, efficient and rapid cluster deployment. Table of Contents What is Bitcoin Mining? ..................................................................................................................... 3 Industrial-Scale Bitcoin Mining of Today ......................................................
Words: 4645 - Pages: 19
