Data Analytics Essay

VII. MULTIMEDIA BIG DATA MANAGEMENT PROCESSING AND ANALYSIS After categorizing multimedia big data, the next important phase in the data management cycle is its processing and analysis. So far, the possible types, sources and perspectives of multimedia big data have been highlighted; but this is only the first of the necessary stages in big data management. Generally, the stages involved in big data processing and analysis include data acquisition, data extraction, data representation, modeling

for African-Americans. Johnson Products had two divisions in their hair line. One was Ultra Sheen, the other was the natural hair line marketed as Afro-Sheen. The slogan was, soul food for the natural. However, there is not a lot of statistical data to support what is known. The sale of relaxers is on the decline. Since hair maintenance is not optional, it is safe to assume that if relaxers are on the decline, then natural hair products are on the rise. This is a booming market. The research

Background There are two aspects of an analytics i.e. Discovery and Communication. Discovery is all about identifying patterns in data. Whereas, Communication provide insights in a meaningful way so that the decisions can be made effectively to increase sales and make company more efficient in terms of cost or human resource saving. Broadly, there are two types of Analytics i.e. Business/Cube Analytics and Predictive Analytics. Business Analytics is a traditional way where historical measures (revenue

amount of data being generated nowadays has increased tremendously. With these large volumes of data, there is a need for efficient storage and processing of data. The data generated from a variety of sources like Social networking sites, Emails, audio and video files, text files and other various files is unstructured. The traditional database cannot handle this complex and high volumes of data efficiently. The Hadoop framework provides an effective solution for storing large volumes of data and processing

FINAL REPORT FOR SUMMER INTERNSHIP WITH AUDIENCE PARTNERS Varun Pillai (267) 471-2511 E-mail: vrp36@drexel.edu Facility: Audience Partners 414 Commerce Drive, Suite 100 Fort Washington, PA 19034 Supervisor: Alex Gochtovtt Chief Analytics Officer Phone: +1-484-928-1010 Fax: +1-484-556-4161 E-mail: alex.gochtovtt@audiencepartners.com Faculty Advisor: Dr. Paul Jensen Associate Professor Associate Dean for Graduate and Undergraduate Programs Dornsife Office for

someone’s whole family tree? This is the type of scenario that represents the different facets of Big Data. What does it mean to say “big data”? Big Data is more than just massive amounts of data stored together. It is more than just data delivered or analyzed fast. Meta Group’s Doug Laney described it as data that has volume, velocity, and variety (2001). This is the 3 V’s of Big Data and is widely used to define it. Additions to this definition include other V’s, such as veracity and

Prescriptive analytics provides the instruction of what to do – and—just as importantly – —what not to do when analytical models are deployed into production environments. Defined as decisions, they are applied to scenarios where there are too many options, variables, constraints, and data for a person to evaluate without assistance from technology. These prescriptive decisions are presented to the front-line worker – —providing the answer they seek, and accounting for the detailed aspects of

The latest driver of business is data analytics. Essentially organizations are poised to use the data they collect about their consumers to help them learn more about their customers and develop new products to meet demand. How is all of this data being collected? One method is by way of enterprise application software. Enterprise application software is computer software used to satisfy the needs of an organization rather than individual users. Enterprise application software is now central

SUMMARY This paper explains the need of a sophisticated Cyber Defense system in organizations and Government agencies and how this can be achieved by using Cyber Analytics. INTRODUCTION Today’s “Cyber Domain” is growing rapidly to keep pace in an ever more competitive world. Businesses are adopting new ways of doing Business due to the increasing dependency on networked communication devices, network access points and cloud-based services. Building a sophisticated Computer Network Defense (CND)

companies to have more data and less accurate analyses. Avinash Kaushik (2007) states that, “ Websites are massively complex, and although tools can capture all the data, they don’t actually tell you what to do” (P.46). I believe that all the data collection should lead to its analysis, and the analysis should produce recommendations. In order to produce the best recommendations, each company needs skilled people with the right analytical intelligence to interpret the data available and produce information