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Mastering Business Intelligence with MicroStrategy

You're reading from Mastering Business Intelligence with MicroStrategy Master Business Intelligence with Microstrategy 10

Product type Paperback

Published in Jul 2016

Publisher Packt

ISBN-13 9781785884405

Length 396 pages

Edition 1st Edition

Tools

MicroStrategy

Concepts

Business Intelligence

Authors (4):

Neil Mehta

Himani Rana

Ning Ma

Dmitry Anoshin

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Table of Contents (13) Chapters

Preface

1. Getting Started with MicroStrategy FREE CHAPTER

2. Setting Up an Analytics Semantic Layer and Public Objects

3. Building Advanced Reports and Documents

4. Advanced Visualization Techniques

5. Customization of MicroStrategy

6. Predictive Analysis with MicroStrategy

7. Accelerating Your Business with Mobile Analytics

8. Data Discovery with MicroStrategy Desktop

9. MicroStrategy System Administration

10. Design and Implementation of the Security Model

11. Big Data Analytics with MicroStrategy

12. MicroStrategy Troubleshooting

Desktop versus Tableau

Tableau is an absolute leader in Self-Service data discovery BI. However, MicroStrategy hugely invests in Desktop in order to be on the same level with Tableau. According to the magical quadrant 2016, Tableau is an absolute leader in self-service BI. According to my experience, MicroStrategy is the best in the Enterprise BI. If you are thinking about what tool to use, it will depend on the business case. If there is a requirement for a huge BI platform that should be scalable and have strong security then go for MicroStrategy. If we need quick results, agility, and flexibility then go for Tableau. And we should remember the latest trend in BI - use bimodal models. For example, we should give opportunities to users which have strong governance and a centralized BI platform with self-service data-discovery agile BI.

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Authors (4)

Dmitry Anoshin

Dmitry Anoshin

Dmitry Anoshin is a data-centric technologist and a recognized expert in building and implementing big data and analytics solutions. He has a successful track record when it comes to implementing business and digital intelligence projects in numerous industries, including retail, finance, marketing, and e-commerce. Dmitry possesses in-depth knowledge of digital/business intelligence, ETL, data warehousing, and big data technologies. He has extensive experience in the data integration process and is proficient in using various data warehousing methodologies. Dmitry has constantly exceeded project expectations when he has worked in the financial, machine tool, and retail industries. He has completed a number of multinational full BI/DI solution life cycle implementation projects. With expertise in data modeling, Dmitry also has a background and business experience in multiple relation databases, OLAP systems, and NoSQL databases. He is also an active speaker at data conferences and helps people to adopt cloud analytics.

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Neil Mehta

Neil Mehta

Neil MehtaBSc (Hons) has 20 years of experience as a developer, analyst, and program manager and has spent the last 7 years specifically implementing business intelligence solutions to help companies leverage their corporate data. Trained in all aspects of analytics from data modeling to system architecture and reporting, Neil currently manages a large team of data architects, ETL developers, and report designers for a large insurance company.He has extensive experience with business analytics, administration, and dashboard design and has helped develop programs to establish super user communities and develop training plans. He has worked in multiple business segments, including financial, oil and gas, transportation, and retail industries.

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Ma

Ma

Ning Ma is an experienced data analyst working in an insurance company. He is experienced with statistical modeling, creating executive dashboards, fraud detection, text mining and teaching. He is also knowledgeable about implementing predictive analysis in MicroStrategy. He enjoys helping business users discovering knowledge from data, by visualizing data patterns and testing hypotheses. He is passionate about producing easy-to-use data products to support business decision making. Prior to his current position, he worked in China doing IT and investment jobs. He did his computer science and economics undergraduate studies in Beijing, economics and finance graduate studies in Canada, and did research on quantitative finance in Canada. In his free time, he loves reading, electronic arts, and all kinds of outdoor activities.

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Rana

Rana

Himani Rana is a senior data scientist and has been working as database developer and MicroStrategy specialist for multinational companies since 2007. She is currently pursuing her PhD in data mining and big data. She completed her master's in data mining and vehicular ad hoc networks. She has to her credit the following publication: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6557928. Himani possesses in-depth knowledge of Business Intelligence and big data technologies. She specializes in insurance and financial data analysis because of her Chartered Insurance Professional (CIP) designation. In addition, she was a committee member and reviewer of Information Systems, Technology and Management (http://www.springer.com/gp/book/9783642291654) and 2011 Third International Conference on Advanced Computing (ICoAC) (http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6156880).

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