WHAT IS TECHNOLOGY TO DATA ANALYSIS


WHAT IS TECHNOLOGY?
Technology is the making, usage, and knowledge of tools, machines, techniques, crafts, systems or methods of organization in order to solve problem or perform a specific function. Technologies can also refer to the collection of such tools, machinery and procedures. Technologies importantly affect human as well as other animal species ability to adapt to their natural environment.
The word technology comes from the Greek words, technologia and from techne, meaning art, skill, and craft. The term can either be applied generally or to a specific areas; for instance, construction technology, medical technology, and information technology. For the purpose of the above course of study (computer in education), we would concentrate more on information and communications technology (ICT).
ICT (information and communications technology-or technologies) is an umbrella term that includes any communication device or application, encompassing; radio, television, cellular phones, computer and network hardware and software, satellite systems and so on, as well as the various services and applications associated with them, such as video conferencing and distance learning. ICTs are often spoken of in a particular context, such as ICTs in education, health care, or libraries. The term is somewhat more common outside of the United States.

SOME IMPORTANCE OF ICT
The use of ICT makes ongoing data collection, data consumption, data based decision-making a more genuine and important proposition, and it can keep these important aspects of analyzing from monopolizing teacher’s time. Modern information and communication technologies have created a “global village”, in which people can communicate with others across the world as if they were living next room. For this reason, ICT is often studied in the context of how modern communication technology affects societies. Previous research found that the use of ICT substantially facilitated collecting, magazine, and analyzing educational data (McIntire, 2007; mc leod, 2005; pierce 2005, wayman 2005).
Therefore technology enhanced assessment (TEA) would likely support data analysis, but applying technology to other aspects of data computing will enhance the implementation of those other components as well. Many large organizations have large amounts of data which has been collected and stored in massive data sets which needs be processed and analyzed to provide business intelligence, improve products and services for customers, or to meet other internal data processing requirements by which technical processes are adopted. For example, internet companies need to process data collected by web crawlers as well as logs, click data, and other information generated by web services.

DATA ANALSIS
Data analysis is a process of inspecting, cleaning, transforming, and modeling data with the goal of highlighting useful information, suggesting conclusion and supporting decision making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, in different business, science and social sciences domains.
Data mining is a particular data analysis technique that focuses on modeling and knowledge discovery for predictive rather that purely descriptive purposes. Business intelligence covers data analysis that lies heavily on aggregation, focusing on business information.

PROCESS OF DATA ANALYSIS
Data analysis and computation is a process that uses technological software within which several phases can be differentiated.
Data clearing;
Data clearing is an important procedure during which data are inspected, and erroneous data are if necessary, preferable and possibly corrected. Data clearing can be done during the stage of data entering. If it is done, it is important that no subject decision can be made.
The guiding principle provided by Ader (ref) i.e. during subsequent manipulations of the data, information should always be cumulatively retrievable in other words; it should be always be possible to undo any data alterations. Therefore, it is important not to throw information away at any stage in the data clearing phase. All information should be saved (i.e., when altering variables, both the original values and the new variables should be kept either in duplicate data set or under a different variable name), all alteration to the data set should be carefully and clearly documented, for instance in a syntax or a log.

COMPUTING AND ANALYSING DATA USING TECHNOLOGY
Using technology to compute and analyze data is a process by technological means; computer programs are used to enter data and summaries, analyze or other wise convert data into usable information. The process may be automated and run on a computer. It involves recording, analyzing, sorting, summarizing, calculating, disseminating and storing data, because data are most useful when well presented and actually informative. Data processing system are often referred to as information systems
The term data processing system and information system are roughly synonymous, performing similar conversion; data processing system typically manipulate raw data into information and likewise information systems typically take raw data as imput to produce information output.

3 responses

  1. Pingback: The great data analysis swindle - GeekErgoSum

  2. Pingback: The great data analysis swindle | Geek Ergo Sum

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s