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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

View More author details

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

BI architecture

BI is all about delivering timely and relevant information to the right level of audience, which helps them to make an appropriate decision. In this section, we will learn about BI architecture and the components involved in it.

Components of BI architecture

Components of BI architecture

Source system: This is any stored data that will be used for BI projects. It could be a database, mainframe system or flat files, or any other system that stores Online Transaction Processing (OLTP) data. This is where data is stored in its raw form.

ETL: This process then pulls the data from the source system and prepares it for the data warehouse. It involves three steps:

Extract: The process of reading data from source systems
Transform: The process of converting data from its previous form to the form it needs to be in, either by combining data from multiple sources or by applying business rules and logic
Load: The process of writing data into the target database, that is, the data warehouse

Data warehouse: This is...

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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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