Business Intelligence & Analytics

Business intelligence (BI) is the set of techniques and tools for the transformation of raw data into meaningful and useful information for business analysis purposes. Big Data is used most extensively today with business intelligence and analytics applications. Big Data can dramatically enhance key areas in Insurance, HealthCare & Banking such as fraud analytics, customer analytics, and web analytics. Techcusp can influence clients about secured data organization and analysis strategies to turn data into knowledge so they can make informed decisions.

Business intelligence (BI) represents the tools, systems and software that play a key role in the strategic planning process of the corporation. It does not replace current analytical infrastructure, but extends its scope: it has become conceivable to conduct analyses based on all data, not just a sample. BI Platform provides platform for ad hoc query and analysis, dashboards, enterprise reporting, mobile analytics, scorecards, and predictive analytics.

Big Data – BI & Analytics Tool & Technologies

• Hadoop
• Ambari 
• Cascading
• Falcon 
• Flume 
• HBase
• Hive
• Knox 
• Mahout 
• Oozie 
• Pig 
• Solr 
• Sqoop 
• Storm
• ZooKeeper

Leading BI Vendors

• Actuate Corporation
• Alteryx
• Excel Power Pivot
• Expression Blend
• IBM COGNOS
• IBM SPSS
• Information Builders
• Kendo UI
• Logi Analytics
• Microsoft Business Intelligence Studio (SSAS, SSRS, SSIS)
• MicroStrategy
• Oracle
• QlikTech
• SAP
• SAS
• Tableau
• Telerik (for ASP.NET & SilverLight)

Apache™ Hadoop®

Apache™ Hadoop® is an open source software that enables the distributed processing of large data sets across clusters of commodity servers. It is designed to scale up from a single server to thousands of machines, with a very high degree of fault tolerance. Hadoop has moved far beyond its beginnings in web indexing and is now used in many industries for a huge variety of tasks that all share the common theme of lots of variety, volume and velocity of data – both structured and unstructured. It is now widely used across industries, including finance, media and entertainment, government, healthcare, information services, retail, and other industries.

Instead of relying on expensive, proprietary hardware and different systems to store and process data, Hadoop enables distributed parallel processing of huge amounts of data across inexpensive, industry-standard servers that both store and process the data, and can scale without limits. With Hadoop, no data is too big.

Database Systems

• Microsoft SQL Server
• Microsoft Access
• Oracle 8,9, 10
• MySQL
• IBM DB2
• Sybase

Key Terms in Big Data

• BI Software
• BI Systems
• BI Technology
• BI Tools
• BizTalk Integration
• Business Analytics
• Business Intelligence
• Business Intelligence Analytics
• Business Intelligence Software
• Business Intelligence Solution
• Business Performance Management Software
• Cloud BI
• Cloud Business Intelligence
• Compliance Reporting
• Dashboards
• Data Analysis
• Data Discovery
• Data Governance
• Data Integration
• Data Integrity
• Data Profiling
• Data Quality
• Data Quality Management (DQM)
• Data Visualization
• Data Warehouse
• Data Warehousing
• Database Integration
• Decision Support System
• eBusiness
• Enterprise Application Integration
• Enterprise Data Quality
• Enterprise Reporting
• ERP Integration
• ESB (Enterprise Service Bus)
• ETL (Extract Transform Load)
• ETL Software
• ETL Tools
• Hadoop
• MDM (Master Data Management)
• Messaging Integration
• Middleware
• Mobile BI
• Mobile Business Intelligence
• OLAP (Online Analytical Processing, OLAP Tools)
• Predictive Analytics
• Real-Time Reporting
• Service Oriented Architecture (SOA)
• SOA Adapters
• Social Media Analytics
• Web Services

Why Techcusp for Big Data – BI & Analytics?

Techcusp Big Data- BI Team can employ advanced data modeling techniques to mine the data warehouse for the identification of trends that suggest new business opportunities and follow through with the recommendation of key technology data strategies and products to leverage opportunities. We can/have:

• Expertise in Bigdata environment and proficient programming skills in the Hadoop environment (Map/Reduce, Pig, Hive)
• Communicate insights and recommend areas for further data discovery
• Design and develop ad-hoc analysis based on business requirements
• Deep experience in Experimental Design
• Deep experience in Dashboards
• Fluency with statistical and machine learning algorithms
• Integrate data from a variety of sources
• Knowledge of visualization tools such as Tableau
• Leverage mathematics and applied statistics to impact project activities
• Perform large-scale statistical research, analysis, and modeling