In the past number of years data has grown exponentially. This growth in data has created problems that and a race to better monitor, monetize, and organize it. Oracle is in the forefront of helping companies from different industries better handle this growing concern with data. Oracle provides analytical platforms and an architectural platform to provide solutions to companies. Furthermore, Oracle has provided software such as Oracle Business Intelligence Suite and Oracle Exalytics that have been instrumental in organizing and analyzing the phenomenon known as Big Data.
Big Data is characterized by four key components, volume, velocity, variety, and value. Furthermore, Big Data can come from an array sources such as Facebook, Twitter, call
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For example, let’s say that you are trading in the stock market. There are thousands of companies and millions of customers.The volume of the amount of customer’s information and holdings is vast. The rate and frequency to how quickly that data is generated, we called this velocity. For example, The New York Stock Exchange deals with “1 TB of information during each trading session.” (page 1 McKinsey Global Institute) This terabyte of information is generated in less than a minute. Velocity deals with how fast the data is being generated. The next category we use to describe Big Data is variety. For the most part, the variety of Big Data can come from either traditional formats such as hospitals or non-traditional such as social media format as Twitter. Big …show more content…
However, Oracle provides a couple of systems that can be utilize. The Oracle Business Intelligence Foundation Suite and Oracle Exalytics are two in-databases analytics that can process and analyze vast quantities of data. Oracle Exalytics is an “in-memory analytics machine”. The Oracle Exalytics server provides in-memory analytics that can compute “capacity, abundant memory, fast storage, and fast networking options and also supports direct attached storage options”. Oracle Exalytics provides faster access to memory due to it “several terabytes of DRAM”. This system works hand and hand with The Oracle Business Intelligence Foundation Suite. Due the higher optimization provided by Oracle Exalytics, The Oracle Business Intelligence Foundation Suite provides greater functionality experience for an end user. Some of the suite features include monitoring, hoc queries, and interactive dashboards including mobile app optimization, unifying fragment systems, and providing “a one mind single version of the truth.” Oracle Business Foundation Suite can capture non-oracle and oracle data. In addition, the suite can maintain and withstand thousands of end users accessing applications simultaneously. Oracle Business Intelligence Foundation Suite and Oracle Exalytics provide vital and essential benefits in the world of Big
In 1994, Jim Donehey was brought in to update Capital One’s IT system. His solution was to replace their aging mainframe computers with an object-based system, but this technology had never been used on such a large scale. In contrast, two-thirds of Capital One’s competitors outsourced their IT functions. Within 5 years the company had the world’s largest Oracle database with 23 terabytes of data – winning them the Gartner Group’s Excellence in Technology Award.
Traditional business intelligence tools are being replaced by data discovery software. The data discovery software has numerous capabilities that are dominating purchase requirements for larger distribution. A challenge remaining is the ability to meet the dual demands of enterprise IT and business users.
Some faculties and departments are already using Oracle applications in their day-to-day operations. As time goes by, more and more information users will be working with an application based on Oracle database technology. If you get the opportunity to be a member of an application development team, you will become familiar with the workings of Oracle and relational databases. Other users may have to learn about this popular database management system through their own experience. This article is for our readers who, as of yet, have no access to Oracle databases but have a yearning for learning what they're all about.
In 1977, Larry Ellison, Bob Miner, and Ed Oates founded System Development Laboratories. After being inspired by a research paper written in 1970 by an IBM researcher titled “A Relational Model of Data for Large Shared Data Banks” they decided to build a new type of database called a relational database system. The original project on the relational database system was for the government (Central Intelligence Agency) and was dubbed ‘Oracle.’ They thought this would be appropriate because the meaning of Oracle is source of wisdom.
...g system that supports the scalability of their data. The following is their input on their new proposal to create a new operational insight tool in order to provide a solution to their challenge:
Now days, companies are searching for new ways of gathering data so that they can get useful data in order to make well informed decisions regarding the market they are operating in. Google analytics is considered one of the best tools offers extensive amount of data to business owners for free. However, the success of business is highly depended on how well they can arrange data and customize their collected data corresponded to their business priorities. Google analytics provides beneficial information for companies regardless of their extent of operation.
Davenport, Thomas H., Paul Barth, and Randy Bean. "How Big Data Is Different." MIT Sloan Management Review. N.p., 30 July 2012. Web. 18 Mar. 2014. .
In 2001 , Doug Laney analyst firm META Group ( now the research company Gartner ) has said that the challenges and opportunities in data growth can be described in three dimensions : increased the amount ( volume ) , increasing the speed ( velocity ) and increased in variety ( variety ) . Now Gartner , along with many other companies and organizations in the field of information technology continue to use the " 3V " to be defined Big Data . By 2012 , Gartner added that apart from Big Data on the remaining three properties to " require new forms of treatment to help to make decisions , to explore deep into things / events and optimize the workflow " .
Currently the world has a wealth of data, stored all over the planet (the Internet and Web are prime examples), but it is needed to be understand that data. It has been stated that the amount of data doubles approximately
First of all, business intelligence analysis requires the capturing of information and storing in a single location for effective data analysis. Currently, data analysis is supported by transactional systems, business specific data marts, and other ad-hoc processes. Information is distributed making it difficult and time-consuming to access. Business teams have adapted to this environment by creating user maintained databases and manual “work-arounds” to support new types of reporting and analysis. This has resulted in inconsistent data, redundant data storage, significant resource use for maintenance, and inefficient response to changing business needs.
For the past couple of decades the majority of businesses have wanted to construct a data-driven organization or company. Furthermore, companies around the world are considering harnessing data as a basis of competitive advantage over other companies. As a result, business intelligence and data science use are popular in many organizations today. The increase in adoption of these data systems is in response to the heavy rise in communications abilities the world over. Which, in turn ,has increased the need for data products. Indeed, the Data Scientist profession is emerging to be one of the better-paying professions due to the urgent need of their labor. This paper is going to discuss what business intelligence is all about and explain data science that is usually confused to be similar to business intelligence. I will tackle a brief overview of data scientists and their role in organizations.
System performance is one of the most critical issues faced by companies dealing with vast amounts of data. Companies use database systems and their applications to store, retrieve and handle this data.
Adopting big data can also help the banking industry by saving them from lots of embarrassment resulting from increase in the number of customer which in turn requires banks to improve on their performance. As stated earlier banks are entrusted with lots of information and this information must be safe will be required to be accessed ready and in a timely fashion. The use a normal small database will not be enough to perform this operation and if banks don’t embrace the use of big data they might start to experience failure in there system.