Data Warehousing Training Institute in Chennai

Top Rated Best Institute for Datawarehousing Training in Chennai provided by Real time working Experts. Learn basic through advanced dimensional modeling concepts, DW/BI Lifecycle In Depth, ETL Architecture Fundamentals with real-world ETL process implementations organized in Datawarehousing training institute in Chennai.

Best Data Warehousing Training in Chennai & Data Warehousing Training Institute in Chennai

INTRODUCTION TO DATA WAREHOUSING CONCEPTS

A data warehouse is a database designed to modify business intelligence activities: it exists to assist users perceive and enhance their organization’s performance. it’s designed for query and analysis instead of for transaction process, and typically contains historical knowledge derived from transaction information, however will include data from alternative sources. data warehouses separate analysis employment from transaction work and alter a company to consolidate knowledge from many sources. This helps in:

• Maintaining historical records
• Analyzing the data to gain a better understanding of the business and to improve the business

WHY DATA WAREHOUSES ?

Data warehouses are distinct from on-line transaction process (OLTP) systems. With a data warehouse you separate analysis work from transaction workload. so data warehouses area unit greatly read-oriented systems. they need a way higher quantity of information reading versus writing and change. this allows much better analytical performance and avoids impacting your transaction systems.warehouse system may be optimized to consolidate data from several sources to realize a key goal: it becomes your organization’s “single source of truth”. there’s nice worth in having a homogenous source of information that each one users will look to, it prevents several disputes and enhances decision-making potency.

WHO SHOULD LEARN DATA WAREHOUSES ?

Users of the data warehouse perform data analyses that are often time-related. Examples include consolidation of last year’s sales figures, inventory analysis, and profit by product and by customer. But time-focused or not, users want to “slice and dice” their data however they see fit and a well-designed data warehouse will be flexible enough to meet those demands. Users will sometimes need highly aggregated data, and other times they will need to drill down to details. More sophisticated analyses include trend analyses and data mining, which use existing data to forecast trends or predict futures. The data warehouse acts as the underlying engine used by middleware business intelligence environments that serve reports, dashboards and other interfaces to end users.

SCOPE OF DATA WAREHOUSES ?

A data mart serves the same role as a data warehouse, but it is intentionally limited in scope. It may serve one particular department or line of business. The advantage of a data mart versus a data warehouse is that it can be created much faster due to its limited coverage. However, data marts also create problems with inconsistency. It takes tight discipline to keep data and calculation definitions consistent across data marts. This problem has been widely recognized, so data marts exist in two styles. Independent data marts are those which are fed directly from source data. They can turn into islands of inconsistent information. Dependent data marts are fed from an existing data warehouse. Dependent data marts can avoid the problems of inconsistency, but they require that an enterprise-level data warehouse already exist.

KEY CHARACTERISTICS OF A DATA WAREHOUSE

The key characteristics of a data warehouse are as follows:

• Data is structured for simplicity of access and high-speed query performance.
• End users are time-sensitive and desire speed-of-thought response times.
• Large amounts of historical data are used.
• Queries often retrieve large amounts of data, perhaps many thousands of rows.
• Both predefined and ad hoc queries are common.
• The data load involves multiple sources and transformations.