Data Analysis : Data And Business Processes

Organizations collect data. This raw data must be analyzed to tease out useful information. The software used to analyze raw data is known as Business Intelligence (BI). BI is comprised of theories and processes such as data mining, online analytical processing, querying and reporting. BI improves decision making, cuts costs and identifies new business opportunities (Mulcahy, 2007). The web data extraction company, Connotate, uses BI systems, specifically dashboards, to focus on more profitable business, saving them time and money while also boosting customer satisfaction rates (6 Real Life., 2013).

The book is all about the things that make one to be a smart consumer of cutting-edge analytics, facilitating to frame the judgement, questioning about the information and the procedure, operating to comprehend the consequences, and using them to progress results for his or her business. Even though it sounds direct, I directly acknowledged it as a deceptively single-minded set of purposes of the book. The writers planned the first half of the book about an analytics outline that entails of six stages: problem acknowledgment, evaluation of previous results, displaying, data assortment and data examination, and outcomes demonstration and action. This planned method to discerning about analytics is one of the most important notions that Davenport

Businesses today have access to significantly more data than any other time in history; however, most businesses are not capturing or using the data effectively. A report by the Aberdeen Group, “The Executive’s Guide to Effective Analytics,” indicates that “44 percent of executives are dissatisfied with the analytic capabilities available to them today, and that they often make critical decisions based on inaccurate or inadequate data” (Forbes, 2014). Luckily, CEO’s are beginning to recognize the need for analytics and more and more businesses are making a shift towards a data-driven business culture.

A new trend has emerged in the modern business environment in which companies are seeking to build what is referred to as "Business Intelligence" or BI for short. This has been viewed as one of the most important organizational priorities for many organizations in the last decade and it is unlikely that this trend will end anytime in the near future. The reason for the BI is pretty clear. Companies have been collecting and warehousing various types of data for many years. BI deals with the means in which companies can make better use of the data; often in real time. This allows companies to better harness information to better support organizational goals and their business objectives. Many of the BI technologies that have developed over the years can deliver better reporting mechanisms, dashboards, and different business metrics so companies can spot various trends and gather insights that can allow the company to ultimately become more competitive. Yet, in spite of the obvious appeal of the benefits a Bi system can offer a company, the development of these systems has been a relatively slow and arduous process. This paper will introduce some of the best practices for current BI systems, as well as some of the possibilities for these systems to further develop in the future.

Today, the world’s trend in operating business focuses on data availability to enact the best suitable decision to improve, develop, and increase business revenues. Moreover, the availability of data helps to monitor and control the quality of provided products or services. However, the availability of data without proper analytics operations would have no meaning (1). Data analytics provide an important aid to an organization to figure out their position in the market in comparison with their competitors. Also, data analytics helps to identify what is the organization’s competitive ability in the market, what they should bet on, and what they should strive for. With that being said, many of today’s most successful organizations utilize

The emergence of big data has provided different avenues for organizations to use data to improve different aspects of their respective operations. Be it customer service, research and development, or market position, Big Data has the potential to be a significant driving force in all these areas. However, there’s still a significant gap between the ability of Big Data to produce insightful analytical information based on real-time data and the ability of organizations to capture and utilize this readily available tool. This is, in part, due to the fact that the systems and processes necessary to fully maximize the usefulness of Big Data is currently lacking in most organizations. This lack of a conducive habitat for Big Data is further magnified in new organizations without any knowledge of Big Data. For organizations that have that have little to no knowledge of Big Data, there must be a thorough assessment of the benefits of big data and how they could improve the organizations overall place in the market. There also needs to be steps taken towards the design of frameworks that will enable the organization to better capture and utilize Big Data.

Business thrive when they have the most accurate, up-to-date, and relevant information at their disposal. This information can be used for a plethora of pertinent markers in small and large businesses, relating to accounting, investments, consumer activity, and much more. Big data is a term used to describe the extremely large amounts of data that floods a business every day. For decades, big data has been a growing field, facing controversy on many levels, but as of late, it has been a major innovator in the challenge of making businesses more sustainable. Big data is often scrutinized for its over-generalization and inability to display meaningful results at times. When applied correctly, data analysis can bring earth-altering information to the table.

It is that time of year again, to sit back, and reflect on everything that has happened in the past year and to make predictions of what will happen in the years to come. The new job that is starting to move out of the woodworks is ‘Big Data.’ These large volumes of data are being used in ways no one could have imagined years ago. Data analysts are using this newly found information to improve the world around us, from helping companies make a more efficient profit, research the climate changes, or improve how people live their daily lives.

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 can be considered as a technology-driven process used for fetching useful and meaningful

Big data is not a hype, but it is the future. The big data industry continues to advance, and big data service providers are making it easier for companies to work with big data in driving their businesses. Progressively, greater volumes and varieties of data will be incorporated with more business processes to support better decision making and greater insight. Moreover,

Data itself is useless, until it is mined and transformed into a valuable source of knowledge discovery. Due to its conversion into useful information, data mining has become the leading source being used in many fields worldwide. “Data mining is based on complex algorithms that allow for the segmentation of data to identify patterns and trends, detect anomalies, and predict the probability of various situational outcomes.”[1] Many organizations from healthcare to multimedia and more are relaying on data and getting developed through the use of it. Regardless of how, data warehouse changed its rhythm and dimension in terms of measurements such as: variety, volume and velocity. Today, one can see the current trends of data mining in different fields such as social networks, healthcare and businesses. As data mining is giving the opportunity for those fields to get advanced, "Big Data" is also opening up new doors within itself as the new trends emerge.

Big data when mined properly can give accurate trends of what products will sell better at what times and to whom these products will sell better to. Big data and data mining when used together properly can significantly boost the decision making and business processes in a business by using management of information systems. Big data can be used for many different things but after it is used and patterns are drawn out of it, the data can be stored in a data warehouse. A data warehouse is a database that stores current and historical data of potential interest to decision makers throughout the company (Laudon, 2013, pp. 225). Databases need to be implemented in companies so they can manage their different customers, sales, suppliers, products, and employees and keep all of their data separate. Databases contain lots of big data but to a human all this data is useless so they need to mine it. Data mining is one of the many complimentary services to big data because it is needed to find patterns and relationships in large databases and

The three Harvard Review Business articles all addressed the revolutionary change in information and how it can be used. The first article describes it as “big data” and calls it a management revolution that helps make better predictions and smarter decisions. Big data is different from the traditional analytics in three ways: volume, velocity, and variety. The volume of data available on the internet is increasing every single day. Companies have so much data they can utilize that most do not know what to do with all of the information. Velocity entails the speed of data today. Real time data allows competitors to compete at the highest level possible and provide customers with what they want faster than before. Variety refers to the fact that data comes

In today’s world, the amount of unstructured data collected is humungous. This unstructured data is of no use if it is not properly processed, analyzed and evaluated. Using this data for the betterment of mankind is what most of the largest companies like Google, Facebook, Amazon, Netflix and much more are targeting. Big data is a term for datasets which are so large and complex that traditional database systems such as MS SQL, MySQL, etc., are incapable of handling them. It is not the amount of data that is important, but what organizations do with data that matters the most. Data can be mapped to useful information which can be further utilized for analyzing and drawing insights that lead to better management practices and strategic