Business intelligence (BI) is 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 opportunities. BI, in simple words, makes interpreting voluminous data friendly. Making use of new opportunities and implementing an effective strategy can provide a competitive market advantage and long-term stability.BI technologies provide historical, current and predictive views of business operations. Common functions of business intelligence technologies are reporting, online analytical processing, analytics, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics and prescriptive analytics.
A basic understanding of dimensional modeling (star schema) for data warehouses.
The ability to create Integration Services packages that include control flows and data flows.
The ability to create a basic multidimensional cube with Analysis Services.
The ability to create a basic tabular model with PowerPivot and Analysis Services.
The ability to create Reporting Services reports with Report Designer.
It is a 20 days program and extends up to 2hrs each.
The format is 40% theory, 60% Hands-on.
It is a 5 days program and extends up to 8hrs each.
The format is 40% theory, 60% Hands-on.
Private Classroom arranged on request and minimum attendies for batch is 4.
Understanding the evolution, need and benefits of business intelligence
Explaining various technical terminologies used with business intelligence
Describing the business intelligence lifecycle and the functions of different management systems in an organization
Illustrating the dependability and integration of ERP, SCM and E-commerce with BI
Detailing the process of data management in an organization
Describing the Usage of BI for Reporting and Querying
Understanding knowledge management and master data management (MDM) application in BI for data management
OLAP (Online analytical processing)
Explaining the evolution, features and functions of OLAP
Detailing the multidimensional analysis for OLAP implementation
Illustrating the concept of data drill-in and drill-up
Describing the various OLAP models as ROLAP and MOLAP and their applications
Understanding executive information system (EIS), key performance indicator (KPI) and dashboards for BI management and control
Describing the process of data design and dimensional modeling in data warehousing
Explaining the process of managing metadata and focusing on the upcoming trends
Detailing the need and techniques for extract, transform and load (ETL)
Explaining the concept of data mining and various techniques like neural networks, decision trees, etc.
Describing the concepts and technical terminologies used in data analytics
Detailing the different techniques used for data analytics like neural network, statistics, fuzzy logic, genetic algorithms, etc.
Understanding data mining and warehousing economics and viability derivation
Illustrating concepts of cost matrix, SLA and ROI applied to data warehousing
Describing the importance of risk mitigation in data mining and warehousing
Understanding the process for assessing the business problem
Explaining the technique to specify desired outcomes and focus pertinent information
Illustrating the data design and architecture design process
Describing considerations for hardware and software selection for BI
Detailing the steps to generate data warehouse matrix and analyze dimensional modeling and ETL for BI
Detailing the process of physical design for implementing BI
Explaining the various physical storage techniques like SAN, RAID, etc.
Describing the different indexing techniques like B-Tree, clustered, etc. for optimization
Understanding partitioning of data and clustering for improved performance
Illustrating steps to select analytics criteria and usage of OLAP tools with data slicing or dicing in implementing BI in an organization
Detailing the concepts and implementation of security policy, user privileges and usage of various security tools
Describing the process for backup and recovery of data
Illustrating the process to monitor and manage data growth in BI
Explaining the technique for performance management by observing dashboards , assessing key performance indicators and using scorecard
Illustrating the future trends in BI as cloud computing, collaboration, mobility, etc.