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Data Science is a field that uses different scientific methods, various algorithms, processes, methods, and systems to extract the information from the unstructured and structured data, and apply the gained knowledge from data across a broad range of application domains. The field utilizes techniques and theories from several other fields like science, mathematics, statistics, information science, computer science, and domain knowledge.
As the use of technology is growing in every field the need to maintain and update their organization through data-driven insights is rising the demand for data science professionals.
The scientific approach in processing huge data resulted in employers increasing the hiring rate of data science professionals.
The rapid demand for data scientists is growing extremely high as the companies understand the great value of Big Data to maintain and to make better business decisions.
Eligibility and Soft skills requirement
Lately, the demand for Data Science has become remarkable. Students started taking extra time for learning Data Science subjects, industry updating skills of their employee staff to be competitive, the course providers and institutes gathered to pick the industry requirements and designed the suitable courses in Data Science.
Now the question arises, what are the eligibility criteria to become a successful Data Scientist? you have our back and here we are with the required Info for the eligibility details of the data science profession.
The students from IT professionals, Engineers, Marketing professionals, software, and students from other IT professional streams or any other external programs can take up part-time in Data Science.
And for the regular course, the basic high school level subjects are the minimum requirement.
Students must have a degree from the related streams – Science, Mathematics, Engineering, and Technology. Studying computer programming in High school is an additional benefit, students study the fundamentals and the advanced concepts in Data Science. Based on the gained basic knowledge in Computer programming, statistics, and machine learning, students become experts in implementing Data Science methods in the practical world.
Soft skills requirement :
- A strong knowledge of statistics, science, mathematics, and programming language.
- Data Visualization.
- Big Data Processing Frameworks.
- Data Extraction, Transformation, and loading.
- Data Wrangling and Data Exploration.
- Good knowledge of at least one programming language – R/ Python.
- Machine learning algorithms.
- Advanced Machine learning ( Deep learning).
Wage: One of the reasons that cause millions of students to become a Data Science professional is the salary, the average salary of a Data Scientist in India is ₹698, 412. An entry-level Data Scientist can make up to 500,000 per annum.
Reasons for the high demand for Data science professionals
According to the reports, there is a high increase in the demand for Data scientists from the last decade and more to increase in the upcoming decade. It’s been studied that a wide variety of industries including the Technology job posting sites and also the non Technology sites have been posting a lot of Data Science posts on their platforms, and this shows the high need for Data Scientists.
The demand for data science has shown drastic changes in recent years. Most employees are preferring to get data science professional jobs. According to the report, it was shown that about 29 percent has increased the demand of the data scientists in the recent year and a 344 percent increase since 2013. This professional is growing dramatically and the organization maintains through data-driven insights.
Here is the valid reason which will count on the demand of data science.
- Most companies are facing a lot of trouble with the handling of the data. Due to the huge amount of data, it has become quite challenging to handle.
- In order to organize the volume of data and to draw meaningful insights from it, the demand of data science experts is required.
- Due to the shortage of skilled resources, data science experts are required to perform analytics and to understand the use of data.
- The demand for data science is increasing because it is hard to find the multi factors. Data science professionals typically are expected to have information related to programming languages.
- The demand for SQL, Apache Spark, and NoSQL database systems is also seen.
- Most of the data science experts come from mathematics, computer science, and natural background. This provides entry barriers for other professionals.
- The best reason for the demand of the data science profession is because the pay is great. The salaries for the positions are given great pay and this Job is among the top-paying in the industry.
- The obligations of a Data Scientist are uncommon and interesting to the work job. The idea of their work permits them to progress in their profession, consolidating different logical abilities over different spaces, for example, AI, large information, and so forth
- The requirement for information science callings is not, at this point, confined to tech monsters. This has at long last driven even mid to little new businesses to look towards information sciences.
- Truth be told, numerous more modest firms hope to enlist section-level information researchers at fair compensation. This functions admirably for both.
- The researcher tracks down a huge ground to sharpen his/her abilities while the association can bear to pay not as much as what it, in any case, would need to.
- Since ventures from assembling to medical care, IT to banking are utilizing information science to some limit, there is no shortage of Data Science Jobs for any individual who is intrigued and will buckle down.
- This isn’t simply restricted to enterprises yet additionally across topographies. Thus, independent of somebody’s topographical situation or current space, information science and investigation is open for everybody to seek after.
Challenges faced with handling data by the companies
- Synchronization across Disparate Knowledge Sources:
Typical big processing includes extraction, transformation, and cargo approach to data integration. Here a bigger part of the info is delivered to a country and synchronous because the data sets are processed in preparation for loading into the target system.
- Handling an outsized Volume of Data
The data explosion is real. Today, data is extraordinary the quantity that may be kept and computed, likewise as retrieved. whereas introducing new process associated storing capacities might not be an issue, managing is.
- Privacy and Security
This is one of the rising issues among several trade experts. Also, as operations grow, many businesses cannot maintain regular checks thanks to the coincident generation of huge amounts of knowledge. Moreover, once it involves aggregation data, privacy laws take issue from one politico-geographic space to another.
- Big knowledge Handling Costs
The management’s immense data, right from the adoption stage to product launch, needs huge expenditure. within the case of the cloud-based platform, too, organizations ought to pay a hefty ad once it involves hiring new workers, cloud services, development, and additionally meet costs related to the development.
- Recruiting and retentive massive data talent
There isn’t any doubt a couple giant shortage of genuinely trained and tough people in big data. though we’ve data scientists, data miners, data analysts, or big data specialists graduating each year. And a major share of these remaining within the pool is uninformed once assigned to extract significant and valuable knowledge.
Lately, the demand for data science became remarkable. Students started taking extra time for learning Data science subjects, industry updating skills of their employee staff to be competitive, the course providers and institutes gathered to pick the industry requirements and designed the suitable courses in Data Science. As the use of the technology is growing in every field the need to maintain and update the organization through data-driven insights is rising the demand for data science professionals.