What is Data Science ?? | Defining and understand what is Data Science

 

Topic Covered:

• What is Data Science?
• Defining Data Science.
• Fundamental of data science.
• Cloud for Data Science.
• Advantages of cloud in data science.
• Data scientist workbench in cloud.
• Data Science helps organizations.
• History of Data Science.

What is Data Science?

Data science is the field of exploring, manipulating and analyzing data and using data to answer questions or make recommendations.

 

Defining Data Science

• Data science is a process, not an event.
• Data science is a study of data.
• Data is real; data has real property we need to study them if we’re going to work on them. Data science involves data and some science.
• It is the process of using data to understand different things, to understand the world.
• Data science is the art of uncovering the insights and trends that are hiding behind data.
• Data science is a field about processes and systems to extract data from various forms of whether it is unstructured or structured form. 

Fundamental of Data Science

        Data science has a significant data analysis component. Data analysis isn’t new. What is new is the vast quantity of data available from massively varied sources:  from log files, email, social media, sales data, patient information files, sports performance data, data sensor data, security cameras and many more besides.

     At the same time that there is more data available than ever, we have the computing power needed to make a useful analysis and reveal new knowledge. Data science can help organizations understand their environments, analyze existing issues and reveal previously hidden opportunities.

         Data scientists use data analysis to add to the knowledge of the organization by investigating data, exploring the best way to use it to provide value to the business. 

Cloud for Data Science

    Cloud is a godsend for data scientists primarily because you take your data, take your information, and put it in the cloud; put it in the central storage system.

    It allows you to bypass the physical limitations of the computers and the systems you are using. And it allows you to deploy the analytics and storage capacities of advanced machines that do not necessarily have to be your machine or your company’s machine.

    Cloud allows you not just to store large amounts of data on servers somewhere in California or in Nevada, but it also allows you to deploy very advanced computing algorithms and the ability to do high performance computing using machines  that are not yours. So think of it as you have some information, you can’t store it, so you sent it to storage space, let’s call it Cloud and the algorithm that you need to use you don’t have them with you, but then on the cloud you have those algorithms available.

    So, what you do is you deploy those algorithms on very large data sets and you are able to do it even though your own systems, your own machines , your own computing environment would not allows you to don so cloud is beautiful.

    And the other thing cloud is beautiful for is that it allows multiple entities to work with same data at the same time. So, you can be working with the same data that your colleagues in say, Germany and another team in India and another team in Ghana, they are collectively working and they are able to do so because the information and the algorithms, and the tools, and the algorithms and the tools and the answers, and the results, whatever they needed is available at a center place which we call cloud.

Advantages of cloud in Data Science

• You don’t have to maintain it.
• You don’t have to download it.
• You don’t have to worry about updating it.

    (All is being done for you in the cloud by the Data Scientist Workbench.)

Data Scientist workbench in cloud

    Data science workbench is an internet- based solution. You log in and the moment you log in, you now have access to some very advanced computing environments. At simple as R in RStudio, and data and algorithms to define the data set using OpenRefine, but also ability to work with very large data sets using technologies, like Spark.

    So, the advantages of working with data scientist workbench is not only that you have the ability to work with these advanced algorithm into computing platforms, but you also have the ability to work with very large data set , because Spark is integrated and it’s all in the cloud.

Data Science helps organizations

• Data science understands their environment.
• Data sciences analyze existing issues.
• Reveal previously hidden opportunities.