Analysis and storage are the two important challenges for organizations large and small. Firstly the amount of Big Data generated has accelerated tremendously. Storing this data economically and securely is one of the top priorities of an organization which is where the Cloud comes into the picture. This has given rise to the trend of hiring skilled data analysts, data engineers, and above all data scientists.
Apart from various skills which a data scientist must possess like analysis, statistics, and programming, he/she is also expected to work on newer platforms in which the organization stores data.
Importance of Data Science with Cloud Computing
Data science and cloud computing essentially go hand in hand. A Data Scientist typically analyzes different types of data that are stored in the Cloud. With the increase in Big Data, Organizations are increasingly storing large sets of data online and there is a need for Data Scientists. To get in-depth knowledge on Data Science, you can enroll in a live Online Data Science Training by Edureka with 24/7 support and lifetime access.
Let us look at the types of data that a data scientist is likely to work in the cloud:
- Look at structured, semi-structured, and unstructured data
- Look at varied sets of data, irrespective of the size, format, etc.
- Analyze them to draw insights
However, the problem with such data is, it often sits in disparate silos. Given that the storage is now much cheaper, and the open-source platforms and tools are available for data scientists, the cloud is the key.
Cloud Computing and Data Scientist?
- Cloud computing can help a data scientist use platforms such as Windows Azure, which can provide access to programming languages, tools and frameworks for free and a fee.
- Data scientists typically are comfortable in using MapReduce tools, like Hadoop to store data, and retrieval tools, such as Pig and Hive. They also use other languages such as Python and Java to write programs.
- Typically, it is seen that data scientists use two types of tools – the open-source ones, such as R, Python, Hadoop frameworks, and several scalable machine learning tools and other more commercially available ones like MS SQL, Tableau, Oracle RDB, and BusinessObjects.
- Given the size of the data sets and the availability of tools and platforms, the understanding cloud is not just pertinent but critical for a data scientist.
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Internet of Things
According to Gartner, there will be about 26 billion devices on the Internet of Things by 2020. Just imagine the data generated by this interconnection; and most of it will be available on cloud. Therefore, there is a need for flexibility, multiple processing systems and disparate data sets, and data science is well entrenched with cloud computing.
Data Scientists are among the most sought-after people when it comes to working on Big Data & Analytics. A simple comparison with other professions will clearly show how things are changing.
The skill set required for data scientists is extensive, and there is clearly a shortage of such skills, so the compensation is extremely competitive. According to a survey by Burtch Works, the average salary for a data scientist with below 3 years of work experience could be about $90,000, whereas at the managerial level, it could go up to $160,000 and more. The compensation at a managerial level for a data scientist is more competitive than for a Mid-level Big Data Professional as per the chart which further reiterates the fact that data scientists have a bright future.
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Future of Data Science & Cloud Computing
At a time when organizations are investing maximum resources in two aspects to remain profitable: Big Data and making sure that the data stays in the cloud. Processing data and shifting it to Cloud organizations avails two benefits, including tackling large data sets for decision-making and reducing the overall cost of infrastructure. Both are here to stay with a huge demand in both fields and billions of dollars of investment.
If you want to work as a cloud engineer or start your career in cloud computing, now is the time to do it. You may become a successful cloud engineer by obtaining the necessary qualifications. You may also take an online Cloud Computing Course.
Also, Edureka has a specially curated Data Science with Python Course Online that helps you gain expertise in Machine Learning Algorithms like K-Means Clustering, Decision Trees, Random Forest, and Naive Bayes. You’ll also learn the concepts of Statistics, Time Series, Text Mining, and an introduction to Deep Learning. New batches for the Data Science course are starting soon!!
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