Design And Delivery Of Highly Scalable And Stable Systems Essay

As we discuss the possibility of emerging into business intelligence software we must keep in mind the overall purpose of using any type of software is to reach strategic goals in order to increase market shares. I will discuss how business intelligence software will allow us to meet those strategic goals. We will establish what type of information and analysis capabilities will be available once this business intelligence software is implemented. We will discuss hardware and system software that will be required to run specific business intelligence software. Lastly, I will give a brief synopsis on three vendors (IBM, Microsoft Microsoft and Oracle) that are dominating the business information software

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.

TDWI is a research division who focuses on high-quality educational research on business intelligence (BI), and data warehousing. TDWI conducted a report which was designed to “educate technical and business professionals about new business intelligence, technologies, concepts, or approaches that address a significant problem or issue.” They also mention how users could discover data relationships that are hidden behind unappealing data structures by using data visualization software’s. These software’s don’t necessarily have to be used by professionals who have been working with business intelligence and analytics for a long time. They are designed to also be used by “nontechnical” individuals who have the curiosity and interest in

Data Base 2 (DB2) Warehouse is IBM’s BI software. The BI software focuses on data warehousing, consolidating data from unrelated sources and forms a “single version of the truth” (IBM.com, 2007), available to users through a variety of analyses. DB2 Warehouse is built to manage mixed workload, run queries concurrently, and also pre-aggregate related data for improved query performance. DB2 Warehouse capabilities include modeling, data mining and visualization, and embedded analytics and database management tools. DB2 has an integrated compression that has proven a savings of 45-69% disk space, and a workload control that automatically prioritizes and schedules queries. In addition to basic data warehousing and mining, IBM has prepackaged solutions for specific industries: banking, retail, insurance, healthcare, telecommunications and law enforcement. DB2 Warehouse will serve clients running Microsoft® Windows® XP or 2000, and run on servers with any of the following operating systems: IBM AIX® 5L™, Red Hat Enterprise Linux® 3 and 4, SUSE Linux Enterprise Server 9, Sun Solaris 9, Microsoft® Windows® Server 2003. It is compatible with two web browsers: Microsoft® Internet Explorer and Mozilla Firefox.

Big Data is an outgrowth of the proliferation of databases and massive data sets. The insights needed to more intelligently manage an organization can be found in the myriad of data sets that comprise a Big Data platform. The greatest challenge of Big Data is contextual intelligence supported by integration to legacy, 3rd party and homegrown application systems located throughout an enterprise (Jacobs, 2009). To get ot his level of proficiency in analyzing Big Data sets and databases, enterprises need Business Intelligence (BI) and analytics tools that can parse through terabytes quickly, finding patterns and analyzing massive amounts of data, then distilling it down to key

Business Intelligence is a process which includes different technologies and methods process for analysing data and presenting information which is helpful for top level management.BI includes various tools, application, and methodologies that enable organizations to collect data from internal and external sources, prepare that for analysis develop and run queries against the data and generate different kind of graphs and reports. Business Intelligence can analysis large amount of data easily and affectively .Identifying new threats and opportunities and implementing an effective and profitable strategy based on insight can provide business a market stability and long term stability.

Business intelligence (BI) is the process of gathering enough of the right information in the right manner at the right time, and delivering the right results to the right people for decision-making purposes so that it can continue to yield real business benefits, or have a positive impact on business strategy, tactics, and operations in the enterprises. Business intelligence is a well-established and generally well-known software category that spans a wide range of functional capabilities. Business Intelligence systems are one step

The era that we live in, in the year 2015 is considered the “big data” era. Industries all over the world are analyzing data and determining marketing and business processes to attract consumers. Data analysis which started off on a much smaller scale today can be used in much broader aspects from coupons you receive in your email, to advertisements you see when you use applications on your smart phone data also can be used to determine the frequent of a customer to a particular store or website. These are both processes of data analytics being used and conveyed in a way to attract customers or satisfy consumer needs. Data analysis focuses on finding the specific data to answer your question, understanding the processes underlying the data, discovering the important patterns in the data, and then communicating your results to gain optimal results. Data is not a new concept in any form, the technology of today’s world makes obtaining and analyzing data easier. The recent decades have seen a fundamental change in the model of data analysis. IMB Tech Trends Report (2011) identified business analytics as one of the four major technology trends in the 2010s. According to Chen (2012) Business intelligence began its practice in business and IT communities just a few decades ago in the 1990s. In the 2000s business analytics was introduced to represent the key analytical components in business intelligence. The business intelligence and data analytics previously adopted in an

Businesses today continue to strive and grow in the industry to keep up with the never ending changes in the business they need the tools to obtain information that can be used to make decisions for the business. The decisions to make in a business can consist of knowing what geographic region to focus on, which product lines to expand, and what markets to strengthen in the industry. To obtain the type of information that has the proper content and format that can assist with strategic decisions they turned to data warehousing. It became the new paradigm intended specifically for vital strategic information.

Business intelligence solutions are very significant to an enterprise performance and capabilities at all levels. They help the business to be more efficient, identify new business opportunities and spot areas of cost savings. Timely access to relevant information has been a hindrance to many business successes. The management is always necessitated to base its decision on the full range of information available but the business always has a huge amount of data (IBM, 2014). Due to the current escalating competition that is eroding the business loyal customers, they are required to install

In the current business world, enterprises have developed strategies and technologies which are useful for data analysis of the associated business information. This information obtained is essential in making prudent business decisions. This developed strategies and technologies used for data analysis are known as business intelligence which is abbreviated as BI. Business Intelligence is associated with businesses issues which go around its history, current situation and a future analysis of the trend of business operation. In business intelligence technologies which are key to business survival include; reporting, online analytical processing, data mining, process mining, benchmarking, predictive analysis among others. This essay discusses issues associated with business intelligence, showing an historical background, its software applications, advantages and disadvantages of business intelligence as well as describing the competition that is witnessed between Google and IBM.

Business Intelligence is all about decision making with a data driven approach. It is a broader term and a super set containing tools, architectures, technologies and techniques that leverage insights from data (various problems or business processes) for analysis, querying, reporting and performance improvement. It is based on measuring or analyzing the historical data and past performance for driving insight and answers to questions like “What occurred?”, “How frequently is occurred?” and “Its impact?”. It includes processes and techniques for data collection, data analysis, data sharing, and reporting using dashboards, illustrative reports and interactive visualizations that laymen understand, all in the service better data driven decision making.

Increasing standards, automation, and technologies have led to vast amounts of data becoming available. Data warehouse technologies have allowed the building of repositories to store this data. Improved ETL and enterprise application integration tools have increased the timely collecting of data. OLAP reporting technologies have allowed faster generation of new reports which analyze the data. As of 2010[update], business intelligence has become the art of sieving through large amounts of data, extracting useful information and turning that information into actionable knowledge.[citation needed]

• Over all 4 years of IT experience in analysis, design and development using Hadoop, Java and J2EE.

Design, code and deliver user friendly multi-tier business intelligence solutions and dashboard that utilize data warehouse and data mining technologies.