Understanding Data Science and Its Requirement
With the world dealing with a large amount of data daily, in Petabytes and Exabytes, the actual power of data science shows up. Data has become an unchangeable and integral part of our life. Day to day, we deal with an ample amount of data which can be either structured, unstructured or semi-structured. With that amount of data existing today (and still growing), various trending fields come into existence and gained popularity in recent years. Fields like Data Science, Big data, Machine learning, Artificial Intelligence, IoT and many more.
Basic Information
When it comes to the study of data and performing some operations on that data to get some meaningful information out of it, we have what is referred to as Data Science. It can also be understood by simple words, “science of data”. All trained and professional data scientists are working rigorously in order to gain some or more relevant and needed information through the raw data. For novices, it seems like an ocean and a random set of data in which certain operations or tools are used to find the actual information lying underneath it.
Aspects of Data Quality
l Accurate and Precise: What’s the use of data which is inaccurate and doesn’t include any required information? It means that the data must accurately define the information that it holds. It should be free from any typos or any kind of inaccuracies that may not be necessary for use.
l Complete: The data must be complete in all sense. That means the data should not be left with any types of gaps which may lead to incomplete information. A complete data will provide complete and right information.
l Clean: Clean data means that the data should be free from duplicate or copied values. Since maximum data is unstructured or unorganized at first, but after performing an operation and manipulation, it is standardized, organized and documented.
l Relevant: The data should be related to the objectives of your analysis. If the data is irrelevant, then the results yielded will be useless and will make no sense.
Requisites to be a Data Scientist
As the world knows that data scientists are one of the highest paid people, so the question might arise in the minds of many people that what skills are required to be a data scientist? Good analytical knowledge of data and its manipulation is the basic requirement to be a data scientist. Furthermore, having a command of high-level languages like Python, Java, Hadoop, SQL, R, Apache, etc. will add to your advantage. Also, practical knowledge of Machine Learning and Artificial Intelligence will pave your path in becoming a data scientist. Since data is understood easily in the form of tables, charts, and graphs. So, being a data scientist, you must possess a great data visualization ability.
Resource Box
The demand for professional and skilled data scientist are always high and will continue to grow in the coming future. So, if anyone has a keen interest in learning data science, they can get into this field by getting the best online data science courses.
