Big Data Big Data is a popular phrase used to describe a massive amount of both structured and unstructured data. Big data is difficult to process with traditional database and software techniques because of large quantity of data. Volume, velocity, variability and variety are three characteristics of Big Data. • Volume: Big data implies vast volumes of data. These data is generated by machines, networks and social media the volume of data to be analyzed is massive. Volume refers to the amount of data to be handled. Many organizations are producing large quantity of data internally or externally. • Velocity: velocity refers to the speed of generation of data or how fast data is generated and processed to meet their objectives. The flow of data is massive and continuous. • Variety: Organizations collects variety of data in several ways. Data which are collects by using internally or externally can be structured, semi-structured or unstructured. As a example social media sources, such as face book, blogs and tweets and data coming from sensors can be semi structured or unstructured. This variety of unstructured data creates problems for storage and analyzing data.[5] Big data is important because it enables to analyze large amounts of raw data where it was not practical, either for cost or technology reasons. Big data is the term for a collection of data sets so large and complex, so it becomes difficult to process using on hand database management tools or traditional data processing applications. Big data differs from traditional, transactional data in a number of ways. Those are volume or storage issue, big data is often not relational (Some of the more structured data can be readily put into relational format but unstruct... ... middle of paper ... ... requires massive performance and scalability. But old platforms poor in scaling, loading data, respond, processing capacity for analytics and handling concurrent mixed workloads. Store and analyze approach, and analyze and store approach can be identified as the two main techniques for analyzing big data. Big Data analytics helps to explore hidden correlations, hidden patterns and provide other valuable insights into the data. This analysis helps to data scientists and other users to evaluate large volumes data, which might be left untapped by traditional business intelligence (BI) systems. Big data analytics can provide competitive advantages to organizations. It also help to achieve business benefits such as more effective marketing and increased revenue. The key goal of Big Data analytics is to assist organizations in making superior business decisions. [8]
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
As noted above , Big Data that is a collection of data capacity in excess of those assumed applications and traditional tools . Size of Big Data is increasing day by day , and by 2012 , it size was estimated around a few dozen terabytes to multiple petabytes ( 1 petabyte = 1024 terabytes ) only for a set of data only.
In our text we began our study of physics with motion because motion is a dominant characteristic of the Universe (Kirkpatrick, 21). In class we learned that speed is the distance traveled divided by the time taken, s=d/t. The definition of velocity is very close to that of speed except that direction of an object is also taken into account.
...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:
8.) Data - means facts or information. People use data as a basis for drawing conclusions about the topic or theme they are studying.
If auditors can look at a complete population, they may not have a great defense if they missed a “smoking gun” since they looked at all the data (Alles and Glen). However, this data may not be valid which raises the importance of the auditor understanding where the data came from and how reliable it is. Not only this, it will be interesting to see how standards consider big data evidence. While it most likely will not be as reliable as confirmations, it would be a challenge to figure out how much the auditors could rely on it. Furthermore, higher education would most likely play a role in helping their graduates understand data and how to use technology to be not only more efficient but also ensure they are able to use sound professional judgement while using big data.
The key strategy implementation efforts at Amazon all surround the use of “big data”. Big data is the growth and availability of large volumes of structured/unstructured data. The use of big data has allowed decision making based upon data and analysis instead of past experience and intuition. Big data has directed organizational change in allowing Amazon to expand from an online book store to an internet giant. Revolutionary application of big data has allowed Amazon to create superior service quality while motivating employees by providing real time information to solve customer issues. Big data has strengthened Amazon’s competitive capabilities by pioneering the application of big data and charging a monthly fee to smaller businesses
Google analytics can be applied in big as well as small businesses to support decision-making processes. In sense, each kind of business has its own
In today’s society, technology has become more advanced than the human’s mind. Companies want to make sure that their information systems stay up-to-date with the rapidly growing technology. It is very important to senior-level executives and board of directions of companies that their systems can produce the right and best information for their company to result in a greater outcome and new organizational capabilities. Big data and data analytics are one of those important factors that contribute to a successful company and their updated software and information systems.
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
Effectively, big data provides the companies with the opportunity to know and understand their customers. With Big Data, a company holds a lot of information about their customers, such as their habits, what is the product they prefer, the time they make purchases, how many products they buy and what kind of promotion their prefer. Then they can make a relation with who the person is, age, gender. Thus they can adapt their offer to the customer. If you are a good client, you can have private discount, or more discount. The objective is to know personally your customer to make them feeling unique.
The typical African, whether in a rural farming community or in the bustling city environment, takes great care to see that meals are properly served and eaten. Great attention is also given to how the meals are prepared and what are its constituents.
26). This dish was very simple and did not require too much time, but I was still able to gain an appreciation for the types of meals that are cooked by Moroccans. Many of the ingredients that were incorporated into this dish are also used in a vast variety of dishes within North Africa. The paprika, cumin garlic, parsley, and red pepper flakes gave this dish a unique flavor that is different from typical eggs and vegetables. There was a hint of spice that seasoned the eggs and vegetables perfectly. The eggs were soft and warm, while the vegetables added a slight unique crunchy and soft texture. Although this dish did not incorporate staple ingredients like lamb, bread, or fish, it did incorporate many of the spices and vegetables that are used in many dishes and on a daily basis. I was able to gain a great deal of appreciation for the types of meals that are prepared in a Moroccan
1.3.a. Volume/flow: The total number of vehicles that pass over a given point or section of a lane or roadway during a given time interval. It is the actual number of vehicle observed or predicted to passing a point during a given interval.