Data Warehouse Essay

Business intelligence (BI) merges architectures, tools, databases, analytical tools, applications, and methodologies. It also is context free like DSS. BI deduces the connections between business entities by evaluating copious volumes of historical data which supports decisions. BI has four major components consisting of a data warehouse, business analytics, business performance management, and a user interface.

Business Intelligence (BI) is the consolidation and analysis of internal data and / or external data for the purpose of effective decision-making. At the core of all BI initiatives is a data warehouse to hold the data and analytics software. The data warehouse stores data from operational systems in the organization and restructures it to enable queries and models to extract decision support reports.

A data warehousing is defined as a collection of data designed to support management decision making. Data warehouses contains a wide variety of data that present a coherent picture of the business conditions at a single point in time. Development of a data warehouse includes development of the systems that extract data from operating systems plus the installation of the warehouse database system that provides managers flexible access to the data. The term data warehousing generally refer to the combination of many different databases across an entire enterprise. (webopidia)

A data warehouse is a large databased organized for reporting. It preserves history, integrates data from multiple sources, and is typically not updated in real time. The key components of data warehousing is the ability to access data of the operational systems, data staging area, data presentation area, and data access tools (HIMSS, 2009). The goal of the data warehouse platform is to improve the decision-making for clinical, financial, and operational purposes.

Business Intelligence refers to the variety of systems used by a company to analyze their raw data. The data is stored in data warehouses, in which

Business analytics on the other hand, as defined on Wikipedia (2012, Aug 06) "refers to the skills, technologies, applications and practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning." It goes on to state that, "Business analytics focuses on developing new insights and understanding of business performance based on data and statistical methods." This is in contrast to business intelligence and stated above. Business intelligence answers questions such as what happened, , how often, how many, where the problem is, and what needs to happen next. Business analytics answers questions like why is this happening, what if these trends continue, what might

Design, code and deliver user friendly multi-tier business intelligence solutions that utilize data warehouse/data mining technologies to consume data across various database platforms and data stores.

Business Intelligence information consists of chronicled data, and additionally new information assembled from source frameworks as it is generated, empowering Business Intelligence supports multi-level decision making processes. Initially, Business Intelligence tools were essentially utilized by IT experts and data analysts whose job is to run analyses and generate reports with query results for business clients. Progressively, however, business administrators and workers are utilizing BI software themselves, on account of the advancement of self-administration of BI and data discovery tools

Today there is a new data management challenge that is an effective method for integrating enterprise applications. To learn from history and predict the future, plenty of companies are using Business Intelligence (BI) systems. Corporations have understood the significance of intensifying achievements of the objectives defined by their business strategies through business intelligence ideas.

How much will organizations spend on business intelligence (BI) in 2016? According to Gartner, organizations are projected to spend almost $16.9 billion in 2016. That is an increase of 5.2% over 2015 sales . Business Intelligence plays a big role in today’s business, it now used in every part of the organization from supply chain to human resources (www.gartner.com). This paper will compare two business intelligence software tools. First, I will define business intelligence (BI). Then, I will examine the features of each of the BI tools. Next, I will discuss the pros and cons of each software. This paper will focus on the capabilities and costs for each BI software. Lastly, this paper will indicates which choice was made and an explanation of that choice.

Business Intelligence (BI) is defined by IBM as, “the discipline that combines services, applications and technologies to gather, manage and analyze data, transforming it into usable information to develop insight and understanding needed to make informed decisions.” (IBM.com, 2006) In its most basic form, BI is an umbrella principle that synergizes the core understanding of your business, including all of its facets, and acting on what that foundation is made up of.

Business Intelligence can be defined as the combined form of developing and learning the data that has been collected from various sources and then analyzing it. Business Intelligence is also used to provide the data in an interactive access to the data which enables the business analysts to process out certain analysis by making necessary manipulations in the data. The data that gets manipulated and analyzed includes the historical data along with the current data along with the performance levels and the situations through which the analysts are able to make precious insights that can be used to provide solutions that can result in benefitting the organization. Thus, Business Intelligence is basically taking actions based on the decisions that are taken by considering the transformed or the manipulated data (Turban, Sharda, Delen, King, & Aronson, 2011, p. 08)

Business intelligence can provide companies with accurate data that can be analyzed to support business strategy therefore enabling companies to better predict effectiveness of their business goals and ultimately result in a business profit. “Business intelligence is already in use in many organizations today, by finance departments to analyze financial performance, sales and marketing to identify customer trends, and operations to enhance the efficiency of supply chains. Using real data helps them answer who, what, where, why and when of related performance” (Rylander,2009).

Furthermore, the Gartner website argues that “BI has become a strategic initiative and is now recognised by chief information officers (CIOs) and business leaders as instrumental in driving business effectiveness and innovation,” (Anon., 2007). Gartner also argues that “BI projects were the number one technology priority for 2007” (Anon., 2007). According to the Bill Inmon, data warehouse is “a subject-oriented, integrated, time variant and non-volatile collection of data used in strategic decision making”. Hammergen & Simon, (2009) define data warehouse more simpler by saying that “ Data warehousing is therefore the process of creating an architected information management solution to enable analytical and information processing despite platform, application, organizational, and other barriers.“ It is important to note that data warehouse system is different from relational database. The reasons of that are: (1) In the data warehouse data is stored for long term; (2) DW is designed for high performance for analytical queries; (3) its OLAP (Online Analytical Processing) technology enables to view data in various form; (4) linking between tables are simple (Tushman, 2014). Databases, in contrast, have a low performance regarding data analysis; joins between tables are

Data warehousing is an efficient system which store the past as well as current data used for creating reports. Data warehousing system is used for decision making by analyzing the reports. A data warehouse is a relational database, which is designed for analysis and query. It helps an organization to consolidate and analyze data from different sources and make decision. A data warehouse environment consists of OLAP (On-Line Analytical Processing) engine, ETL (Extraction, Transformation and Loading) process, client analysis tools and other applications that manage gathering and delivering the data.