Name IDMd. Aminul Islam 18-065Habibur Rahman 18-076Pronoy Kumar Bhoumik 17-077Sazzad Ferdous 18-056

BUSINESS INTELLIGENCE AND ANALYTICS (BIG DATA)

ObjectivesWhat is Business intelligence (BI)?Big data analytics.Business intelligent and data warehousing.BI&A Applications.Features of Business Intelligence.Key Characteristics.E-Commerce and Market Intelligence.Data Analytics.

Business intelligence (BI) A set of theories, methodologies, architectures, and technologies that transform raw data into meaningful and useful information for business purposes. BI can handle enormous amounts of unstructured data to help identify, develop and otherwise create new opportunitiesBI and big data analyticsBI is not a new concept. Data warehouses, data mining, and database technologies have existed in various forms for years. Big data as a term might be new, but many IT professionals have worked with large amounts of data in various industries for years.

Big data is growing fast as organizations devote technology resources to tapping the terabytes (if not petabytes) of data flowing into their organizations and externally in social media data and other sources.

Integrating advanced analytics for big data with BI systems is an important step toward gaining full return on investment

Big Data Softwares:Hadoop - Apache FoundationMongoDB - MongoDB, IncSplunk - Splunk Inc

Usage MarketArchitectureResearch activities

Business intelligence and data warehousing

Often BI applications use data gathered from a data warehouse or a data mart. A data warehouse is a copy of analytical data that facilitates decision support. However, not all data warehouses are used for business intelligence, nor do all business intelligence applications require a data warehouse.Business intelligence and analytics (BI&A) and the related field of big data analytics have become increasingly important in both the academic and the business communities over the past two decades

Example-Industry studies have highlighted this significant development. For example, based on a survey of over 4,000 information technology (IT) professionals from 93 countries and 25 industries, the IBM Tech Trends Report(2011) identified business analytics as one of the four major technology trends in the 2010.97 percent of companies with revenues exceeding $100 million were found to use some form of business analytics

BI&A Applications: From BigData to Big Impact(usage)Global business and IT trends have helped shape past and present BI&A research directions. International travel, high-speed network connections, global supply-chain, and outsourcing have created a tremendous opportunity for IT advancementIn addition to being data driven, BI&A is highly applied andcan leverage opportunities presented by the abundant data anddomain-specific analytics needed in many critical and high impact application areas.(1) ecommerce and market intelligence, (2) e-government andpolitics (3) science and technology, (4) smart health

Features of Business Intelligence

Executive dashboardseasily understood real-time data to business leaders, enabling faster and better decision-making whilst lowering response times to internal and external.

Location IntelligenceLocation Intelligence is the ability to map and visualize data in geographical formats.

Features of Business IntelligenceWhat if analysisWhat if analysis allows businesses to assess the potential effects of critical business decision before theyre actually made. Using existing data

Interactive reports Interactive reports help users convert data into knowledge. They allow users to better understand the analysis within

User should be able to: Drill down and through reportsConduct slice and dice OLAP analysisApply analysis such as moving averages and regression to highlight trends in data Meta data layerA meta data layer makes reporting easy and eliminates the need for coding and SQL, allowing users and report writers to see and access information in simple business language

Ranking reportsThis feature allows you to create reports that order specific categories of information, from across multiple source of data.

BI&A Overview: Evolution, Applications, and Emerging Research

Key CharacteristicsBI&A 1.0DBMS-based, structured content RDBMS & data warehousing ETL & OLAP Dashboards & scorecards Data mining & statistical analysis

BI&A 2.0 Web-based, unstructured content Information retrieval and extraction Opinion mining Question answering Web analytics and web intelligence Social media analytics

BI&A 3.0Mobile and sensor-based content Location-aware analysis Person-centered analysis Context-relevant analysis Mobile visualization & HCI

E-Commerce and Market Intelligence

BI&A and Big Data has arguably been generated primarily from the web and e-commerce communities.

Significant market transformation has been accomplished by leading e-commerce vendors such Amazon and eBay through their innovative and highly scalable ecommerce platforms

BI&A ResearchApplications have generated a great deal of excitement within both the BI&A industry and the research

Emerging analytics research opportunities can be classified into five critical technical areas(big) data analytics, text analytics, web analytics, network analytics, and mobile analyticsall of which can contribute to BI&A 1.0, 2.0,and 3.0. The classification of these five topic areas is intended h community.

(Big) Data AnalyticsData analytics refers to the BI&A technologies that are grounded mostly in data mining and statistical analysis. As mentioned previously, most of these techniques rely on the mature commercial technologies of relational DBMS, data warehousing, ETL, OLAP.

Text AnalyticsA significant portion of the unstructured content collected by an organization is in textual format, from e-mail communication and corporate documents to web pages and social media content

Web AnalyticsOver the past decade, web analytics has emerged as an active field of research within BI&A. Building on the data mining and statistical analysis foundations of data analytics.Network AnalyticsNetwork analytics is a nascent research area that has evolved from the earlier citation-based biblio metric analysis to include new computational models for online community and social network analysis

Mobile AnalyticsAs an effective channel for reaching many users and as a means of increasing the productivity and efficiency of an organizations workforce, mobile computing is viewed by respondents of the recent IBM technology trends survey (IBM2011) as the second most in demand area for software development.

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