DataBig Data and Future of Data-Driven Innovation A. A. C. Sandaruwan Faculty of Information Technology University of Moratuwa chanakasan@gmail.com The section 2 of this paper discuss about real world examples of big data application areas. The section 3 introduces the conceptual aspects of Big Data. The section 4 discuss about future and innovations through big data. Abstract: The promise of data-driven decision-making is now being recognized broadly‚ and there is growing enthusiasm
Free Data Data analysis Business intelligence
Environmental Studies For Undergraduate Courses subhamsahu CORE MODULE SYLLABUS FOR ENVIRONMENTAL STUDIES FOR UNDER GRADUATE COURSES OF ALL BRANCHES OF HIGHER EDUCATION Vision The importance of environmental science and environmental studies cannot be disputed. The need for sustainable development is a key to the future of mankind. Continuing problems of pollution‚ loss of forget‚ solid waste disposal‚ degradation of environment‚ issues like economic productivity and national security
Premium Environmental science Pollution Biodiversity
When looking for data‚ it is important that school administration and teachers know what to look for. They can define their search by formulating essential questions with which to answer using the data. The essential questions will lead to goals that the school strives towards by researching the data. Data may include online databases‚ site based databases‚ spreadsheets‚ test scores and various other collection sources. The data can be collected on various online and printed forms used for documentation
Premium High school
Factors that influence the selection of data collection instruments Data Collection is an important aspect of any type of research study. Inaccurate data collection can impact the results of a study and ultimately lead to invalid results. Data collection methods for impact evaluation vary along a continuum. At the one end of this continuum are quantitative methods and at the other end of the continuum are Qualitative methods for data collection. A data collection instrument is a tool for monitoring
Premium Qualitative research Observation Scientific method
MEAN SCORE Descriptive Statistics N Mean Std.Deviation Discount 196 1.38 .672 Gift Coupon 196 1.47 .603 Free tour 196 1.91 .929 Cash back 196 1.44 .634 Price 196 1.54 .753 Quality 196 1.44 .592 Quantity 196 1.58 .715 Varity 196 1.68 .609 Brand 196 1.66 .641 Durability 196 1.94 .732 Availability 196 2.04 .902 Promotion Scheme 196 2.24 .944 Advertisement 196 2.10 .871 Promotional scheme of Berger paint is very attractive. 196 1.99 .791
Premium Standard deviation Brand Statistics
Data Collection Methods. Introduction Data collection is the process of gathering and measuring information on variables of interest‚ in an established systematic fashion that enables one to answer stated research questions‚ test hypotheses‚ and evaluate outcomes. Data Collection Techniques include the following: Personal Interviews Conducting personal interviews is probably the best method of data collection to gain first hand information. It is however‚ unsuitable in cases where there are
Free Sampling Simple random sample Stratified sampling
Distinguish between primary data and secondary data? Primary data is the data that is collected first hand from the original source for the purpose of making statistical inference while secondary data is the data that is collected by the method of abstraction and is used to make statistical inference by using primary data already collected by an investigator. Primary data is collected by Identifying population of interest choosing sample analyse sample information draw inference from
Premium Question Interrogative word Sentence
The Big Data Challenges Lamin A Tunkara CIS 500 – Information Systems for Decision Making Dr. Edwin OTTO July 16‚ 2013 Abstract The paper explores the challenges of big data and the strategies deployed by Volvo Car Corporation in instituting an information technology infrastructural tool that helped the company tap into its massive data‚ bank to extract information for meaningful process improvements. The paper culled information from Dumbill (2012) who in an article
Premium Volvo Cars Data analysis Data
Information gathering is a key element when you are trying to find some hidden data about someone‚ a company‚ or even a school. In a university‚ I could determine what the internet protocol address range by going to a web browser and typing in WHOIS in the search engine. Afterwards I would click the WHOIS link and it will take me to a screen with a text search box where I would put in the domain name of the university and hit search. Then I should see the results and it will give me the university’s
Premium
5.3.3 Data cleaning Data cleaning helps to remove all unnecessary data. Data cleaning attempts to fill in missing values‚ smooth out noise while identifying outliers and correct inconsistencies in the data. Data cleaning is usually an iterative two-step process consisting of discrepancy detection and data transformation. 5.3.4 Data analysis Data analysis is also known as analysis of data or data analytics‚ is a process of inspecting‚ cleansing‚ transforming and modeling data with the goal of discovering
Premium Data Data mining Data analysis