Multimedia Advantages and Disadvantages

MULTIMEDIA SYSTEM

System means the combination of different components which work in coordination with each other in a certain manner so as to serve some specific purpose. Multimedia is the technology which can disseminate two or more different media like text, audio, video, etc in a single time frame. Thus multimedia system means the proper combination of different multimedia components which work together to create, edit, store and disseminate the multimedia components. Almost all of today’s multimedia systems take advantage of power and ease of computer systems. Without computers, today’s sophisticated multimedia cannot be thought of. So, multimedia system could be more accurately defined as the combination of computer hardware and software designed so as to create, store and disseminate the multimedia content.

The multimedia computer generally contains the following components.

1) Computer

2) Multimedia Software

3) Sound card

4) CD-Drive

5) Micro-Phone

6) CD-ROM Disk

7) Multimedia speakers/Head-Phones

8) Digital Camera and many other components.

All of some of the above mentioned components work together to make up the multimedia system which can capture, digitize, compress, decompress, retrieve the multimedia component (multimedia data) and show it into the output devices like Computer Monitor, Multimedia Projectors, etc. Literally speaking, all the components that could be used in the multimedia system are impossible to list out. The above mentioned are only some of the important components of multimedia computer system.

ADVANTAGES OF MULTIMEDIA

We have already mentioned various advantages of using multimedia. We can still specifically list out following points that explains the advantages of the multimedia.

1. It can be used to help students and teacher to teach as well as learn the given topics easily.

2. It can be used to spread the knowledge easily all over the world wide in the cheap cost.

3. It is easy to take the multimedia files from one to other places as it can be stored in the cheap and light storage devices like CD-ROM.

4. It can be used for any subject and for anyone.

5. It can be used in Television, Films Industries and for personal entertainments.

6. It is highly used to realize the concept of Open University, Distance Education System, and Video Conferencing.

7. It is also used in Internet to make up the interactive web-page contents.

8. We can give the everlasting impression to the intended audiences on a specific topic by the use of multimedia.

9. Colored pictures, Motion pictures and other graphics could be shown in monitors and other big screens so that many people could view it and make out the impression about it.

10. Multimedia systems are generally very interactive so it is interesting to use.

DISADVANTAGES OF MULTIMEDIA

In comparison to the enormous advantages we have very little disadvantages of multimedia. These disadvantages could be listed out as:

1. It is expensive to produce multimedia contents.

2. It is expensive to set up the multimedia systems.

3. It needs well trained manpower to create and use it.

4. Multimedia files are too large so, it is time consuming to transfer across the Internet and Intranet.

Hadoop Streaming

Hadoop streaming is a utility that comes with the Hadoop distribution. This utility allows you to create and run Map/Reduce jobs with any executable or script as the mapper and/or the reducer.

HOW STREAMING WORKS:In the above example, both the mapper and the reducer are python scripts that read the input from standard input and emit the output to standard output. The utility will create a Map/Reduce job, submit the job to an appropriate cluster, and monitor the progress of the job until it completes.

When a script is specified for mappers, each mapper task will launch the script as a separate process when the mapper is initialized. As the mapper task runs, it converts its inputs into lines and feed the lines to the standard input (STDIN) of the process. In the meantime, the mapper collects the line-oriented outputs from the standard output (STDOUT) of the process and converts each line into a key/value pair, which is collected as the output of the mapper. By default, the prefix of a line up to the first tab character is the key and the rest of the line (excluding the tab character) will be the value. If there is no tab character in the line, then the entire line is considered as the key and the value is null. However, this can be customized, as per one need.

When a script is specified for reducers, each reducer task will launch the script as a separate process, then the reducer is initialized. As the reducer task runs, it converts its input key/values pairs into lines and feeds the lines to the standard input (STDIN) of the process. In the meantime, the reducer collects the line-oriented outputs from the standard output (STDOUT) of the process, converts each line into a key/value pair, which is collected as the output of the reducer. By default, the prefix of a line up to the first tab character is the key and the rest of the line (excluding the tab character) is the value. However, this can be customized as per specific requirements.

The future of BIG Data

Prescriptive analytics can be seen as the future of Big Data. If we see descriptive analytics as the foundation of Business Intelligence and we see predictive analytics as the basis of Big Data, than we can state that prescriptive analytics will be the future of Big Data. Earlier, I already explained the difference between these three types of analytics, but let’s have a small recap: descriptive analytics means looking at historic data, ranging from 1 minute ago to years ago. It can be compared as looking in the rear mirror while driving. Predictive analytics means using all that data to make a prediction about where to go; it is the navigation that tells you how to drive and when you will arrive. Prescriptive analytics is the self-driving car, that knows exactly what the best route is based on infinite data points and calculations. Not surprisingly, Google’s self-driving car makes extensive use of prescriptive analytics.

Prescriptive analytics uses the latest technologies such as machine learning and artificial intelligence to understand what the impact is of future decisions and uses those scenarios to determine the best outcome. With prescriptive analytics it becomes possible to understand and grasp future opportunities or mitigate future risks as predictions are continuously updated with new data that comes in. Prescriptive analytics basically offers organizations a crystal ball. Prescriptive analytics will become really powerful when it has developed into a stage where decision makers can predict the future and make prescriptions to improve that predicted future, without the needs for Big Data scientists.

Although prescriptive analytics is really still in its infancy, we see more and more use cases being developed. Also several Big Data startups focus especially on prescriptive analytics. The most well know is Ayata. They use patented software to predict what is going to happen, when it is going to happen and why it is going to happen. They focus primarily on the oil and gas industry, but there are more use cases of prescriptive analytics. Prescriptive analytics is used in scenarios where there are too many variables, options, constraints and data sets. Without technology it is too complex for humans to efficiently evaluate those scenarios. Also when experimenting in real-life is too risky or expensive, prescriptive analytics can come to rescue. Let’s have a look at three of the possible use cases: