Cloud Computing

Role of Information and Technology in Data Science and Cloud Computing

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Data analytics has been long used by businesses to give direction to their strategy in order to maximize profits. By tracking data, businesses can eliminate guesswork and instead systematically understand patterns and make informed decisions while implementing new strategies for either business operations, marketing or client acquisition, etc. Alongside analytics, Cloud Computing has also played a major role in making businesses more efficient and operate effectively.

Role of Information and Technology in Data Science and Cloud Computing

The consolidation of Cloud and Data Science could help businesses store, process, interpret their big data to meet both business and client needs.

Cloud Computing

Cloud Computing includes a series of hardware and software that can be remotely accessed and the files and software are usually shared by multiple users. So, rather than being on a user’s hard disk, the files reside on the remote storage.

Data Science

Data science essentially entails the study of where the data originates from and what it speaks to and how this data can be analyzed into a significant asset to operations and business as a whole. Mining a lot of structured and unstructured data is essential to establish associations that will ultimately enable businesses to either work more efficiently, productively or to control costs or perceive a new market, etc.

How do the two technologies work together?

Data science and cloud computing go hand in hand and the two technology implementations will complement each other for better performance and value. With the rapid growth of big data, Data Science has become an inevitable part of businesses that desire to derive value from their existing processes and pave a path for continuous learning and improvement within their processes and organization as a whole. Cloud Computing & Data Science together help businesses stay on top of their game and get better by the day.

Artificial Intelligence

What is AI and How Deep Learning help to grow business

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AI (Artificial intelligence) is making machines intelligent that can perform cognitive tasks like humans and even more efficient than humans with the help of complex computer programming and enormous data fed to get an optimal solution for the problem. Though AI came into existence since 1956, but due to lack of data and technology could not become a reality.

Now proceeding further, there are two subsets of AI, Machine learning, and Deep learning. Machine learning gives computers the ability to learn without being explicitly programmed. Deep learning is a subset of machine learning, where deep artificial neural networks work as human brains and have networks capable of learning – unsupervised, from data that is unstructured or unlabeled.

Let us see how deep learning can help to grow business.

Implementing deep learning can be advantageous in many ways. Consider any following needs of your business be it:

• Interviews and Training: The trained human brains can take better interviews considering the company’s requirement without discrimination and partiality and can train employees for future utilization.

• Time consumption: Humans get tired and need time for refreshments. In the minimum time frame, maximum work can be done through deep learning. The pace at which the machine works is quicker than humans, without break or rest. Hence less time consumed.

• Accuracy: A large amount of data fed and information from the web can provide flawless results whereas humans tend to make silly mistakes easily.

• Customer service: Software robots now also can understand human sentiments which can lead to a quality response to valuable customers of your company which helps to retain present customers and gains prospective customers. If we talk about humans, sometimes due to stress or mood swings fails to give good services to customers.

• Innovations: Like humans, these robots can efficiently think about innovative products and lead towards the development of the company.

• Maintenance: Humans repair machines and things when it is damaged or stops functioning. But with the help of deep learning damaged machines/things are detected before time. So, it can get repaired in advance which can boost the company’s performance.

• Security: Depending on past experience and the company’s informative data software automation can detect frauds instantly which humans may not do every time.

Deep learning can save time, power and cost and perform better than humans in each aspect that can make any company grow not only double but up to ten times more. Deep learning is the future of business and will definitely change how most of the businesses have traditionally operated.

Data Science

How Data Science and R boost the business analytical model

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Building a model for statistical analysis was a daunting task – playing around with C and C++ and painstakingly building a lengthy program. Even if one thing goes wrong, you would have to pull the whole thing down or start all over – a truly crushing realization.

Thankfully, in the world of technology, things move quickly and in the world of statistical analysis, things have moved faster. It’s now possible to create a system for analyzing data that’s constantly adapting, evolving and improving. One of the best ways to do that is with R.


So, what exactly is R?

R is a programming language with rich features and can be used for all kinds of data science, statistics and visualization projects. R’s popularity is also due to its open source nature with an extensive support network and free tutorials. R is known to be so versatile and powerful that everyone from Google to Facebook is using it to either analyze the news feeds or to assess the effectiveness of its ads. R has enough provisions to implement machine learning too.

Benefits of using R

Here are some of the benefits of using R:

  1. The coding is quite easy and can be implemented easily too.
  2. It’s open source and no need to pay any subscription charges – no recurring costs of any kind.
  3. Availability of instant access to over 7800 packages that are customized to perform various computation tasks.
  4. R has an overwhelming community support and there are a number of forums that will help you in case of any issues.
  5. High performance computing experience.

Beginning in the 90’s, a number of endless efforts have been made to improve the interface and the journey of this language from being a text editor to an interactive studio that can enable data science and statistical analysis is quite a journey in itself!