Top 5 technical skills for IT professionals:

Top 5 technical skills for IT professionals:

As we are heading towards 2020 and bid adieu to 2019, its imperative to take a seat back and think how are we going to welcome the technological changes in the coming year. We should also focus on the top 5 technical skills for IT professionals to master technology trends. As we all know, technology is the back bone of our lives and survival without it is not possible. Technology has equally made our life easy and challenging at the same time. For the ease it brings to our lives, it is also important to acknowledge that it’s not a static subject. It keeps on updating and transforming itself. Just like we cannot reinvent the wheel but we can keep on moving it, same way we have to keep ourselves moving and upgrading and be at par with the latest technologies.

While we prepare ourselves to usher in 2020, let’s have a look at some of the top skill sets which are a must now. As we learn more about these technologies, more we are prepared to face the challenges posed by the technological updates.

On that note, let have a look at the top 5 technical skills for IT professionals:

Big Data

Big data is the most talked about technology in terms of its applicability across domains as well as its usability. While it can be made applicable to any industry or domain likewise, its useful also based on its ability to handle any kind of data. We are in an era where everything we do or talk or write is converted to some or other form of data. And the amount of data that is being generated is so huge that any traditional database cannot handle and process it. In this situation, Big Data comes to our rescue. Its potential to handle absolutely high volume of data which can be of any form – structured, semi structured or unstructured-have made Big Data a big yes for any industry and domain.

What is Big Data

Big Data is a technology which provides us with a platform through which we can handle very large amount of data. Also the data can assume any form and source.

If we believe the facts, Facebook generates 4 petabytes of data daily which includes 100 million hours of daily video watch time, 4 million likes every minute. Twitter generates 6000 tweets per second which corresponds to over 350,000 tweets sent per minute, 500 million tweets per day and around 200 billion tweets per year.

These and many other social media platforms generate huge amount of data daily. Such huge data cannot be handled by traditional RDBMS tools. Also the traditional databases can handle only structured data which appear in row/column format. However the data that these social media giants generate are mostly unstructured, like tweets can have any form, videos, photos etc. These are examples of unstructured data. These challenges can be handled by Big Data easily.

How does big data solve these problems

Big data works on the principle of four V’s – Volume, Velocity, Variety, Veracity

1) Volume – As we saw in above paragraph, huge amount of data is generated nowadays which can be handled only through Big Data

2) Velocity – Velocity means the speed at which data is getting generated. As we see in Facebook and Twitter example above, they generates terabytes and petabytes of data daily. This is not possible for traditional databases. Big data can handle it easily.

3) Variety – Variety means the data need not be in a structured format. It can be of any form like text, photos, videos etc.

4) Veracity – Even after handling such level of data, data correctness remains a major concern. Big data is well equipped to maintain the data correctness and provide verifiable data to users.

How does big data works

As we said, Big data provides with a platform to handle huge data with variety of data. Hadoop Framework is the Big Data platform which provides us the solution. Hadoop is an open source, distributed, clustered framework which provides us with components which handles the all the data level challenges. The cluster can have many computers which can be located at any location.

Architecture of Hadoop – Hadoop architecture consists of below components:

1) Hadoop Distributed File System – HDFS is built on top of UNIX operating system. HDFS is the storage component of Hadoop. It stores the data that is being generated via any source. The data is stored in various block format. This means that the data file is divided into a number of data blocks. Those data blocks will be distributed across multiple systems. Minimum data block size is 128 MB. Each data block is also replicated with a factor of 3. This means that each data block will be copied 3 times.

2) Map Reduce – Map Reduce is the programming component of Hadoop. This means that any programming that is being required to be done on the data that is being stored in HDFS. Map Reduce supports Java as well as Python.

3) Yet Another Resource Negotiator – This component is responsible for allocating the cluster resources to various tasks based on the availability.

Conclusion: Big Data is the highly recommended solution if we have a huge amount of data having unstructured data format because of its ability to support various components. Hence Big Data easily makes its way into top 5 technical skills for IT professionals.

Cloud Computing

Have you ever imagined to be able to code on Python without actually having a relevant platform or be able to save you important data without actually owing a storage system. Cloud Computing is the solution then. Cloud computing is the on-demand availability of various resources like storage, processing, computing without the user actually having ownership of any of these resources. Cloud is actually used to refer to the data centres located across internet irrespective of the location of user. Hence the term cloud is being coined to represent availability of the resource to any one at any place. Clouds can be private( organisation specific) or public(for multiple organisations). Looking at its benefits, its no wonder that Cloud Computing is a part of top 5 technical skills for IT professionals.

Advantages of Cloud Computing

  • This gives us a flexibility to use the resource without actually installing them. This saves a lot of infrastructure cost.
  • We can also save a lot of money in buying multiple licenses of a single software. For example, instead of buying 10 licenses of a X software, a company can buy 5 licenses. And 10 people can use them via cloud because not all 10 users will be using the software at the same time because of different location and time zones.
  • It also makes application to run faster with less down time and less maintenance.

Cloud provides below three service models

1) Infrastructure-As-A-Service: This service model provides various infrastructure related resource to users like virtual machines, servers, storage.

2) Platform-As-A-Service: This model provides various development environment to the developers like database, web server, development environment, development tools

3) Software-As-A-Service: Through this model, user gains access to various software and tools for their requirements like CRM, email, virtual desktop, games etc.

Major Cloud service providers

Microsoft Azure, Google Cloud platform, Amazon Web Services

Conclusion: For any enterprise to survive and work towards reducing cost, Cloud Architecture is a must.

Agile

In short Agile is way of providing continuous update about the on-going software development or testing process. It is iterative in nature and provides periodic view of software code in terms of modules. It is a practice of continuous iteration of development and testing life cycle. Gone are the days of waterfall model where entire software product was delivered in one go. This had the disadvantage where in only at the delivery, it becomes visible whether the software has met client expectations or not. Through Agile, client is continuously made aware of the ongoing work and any changes and updates can be accommodated easily.

The agile software development emphasises on four core values

1.Individual and team interactions over processes and tools – More focus is being given to individual interactions to solve the impending issues and problems.

2.Working software over comprehensive documentation – Teams strives to deliver working software to the client instead of focusing on prolonged documentation. Documentation eats up a lot of time and energy. hence only limited documentation is done.

3.Customer collaboration over contract negotiation – Under agile, periodic customer engagements are being done to get their feedback and work on the updates provided by the client.

4.Responding to change over following a plan – In case during the periodic review, if there are any concerns raised by the client, then immediate actions are being taken and such requests are being handled easily.

There are many flavors of agile that are in use in the market today

1) Scrum

2) DSDM – Dynamic Software Development Method

3) Extreme Programming

4) Feature Driven Development

5) Lean Software Development

6) Crystal Methodologie

Conclusion: Agile provides a better way of achieving customer satisfaction. Hence adopting Agile is a must now. No employee from IT industry will keep Agile out of the list of top 5 technical skills for IT professionals.

Artificial Intelligence and Machine Learning

Both these terms are being used together and interchangeably but they do differ about their application. Artificial Intelligence is a broader concept of enabling a non-human or a non-natural thing to perform some tasks or activities by itself without human intervention.

Machine Learning is an application of AI based on idea that we should be able to give access of data to machines and let them act and learn by themselves.

One of the main reason why AI is picking up pace now a days is that the industry wants to reduce human effort and replace it by some sort of automation. Now automation is something which when executed well reduces manual effort. But automation is limited in its applicability because automation is nothing but a piece of code which will do what is being coded. It cannot enhance or upgrade by itself.

On the other hand, AI provides the machine an ability to act, behave by its own. On top of this, learn and upgrade by itself based on the experiences it faced in the past much like we humans do. We all know that humans behave and react based on their wisdom and learning that they acquire based on their experiences. Artificial Intelligence to enable machines to learn and adapt themselves. Machine Learning just applies this logic to machines to enable them to be AI enabled.

Python

No one can beat when it comes to programming and development. Since programming and development are those areas which are always expanding and always full of opportunities. Nothing excites the developers more than coding. While there are many programming languages available in the market, Python is one language is quickly picking up pace and is on its way to become one of the most used programming languages of time.

The design of Python was started around 1980 by Guido van Rossum. Python is object oriented, structured programming language with dynamic semantics. Python is highly readable language due to its easy syntax and hence reduces the learning time. Its fast because there is no compilation step. Its direct edit-test-debug cycle reduces the time to code and execute. This dynamic binding makes it attractive for Rapid Application Development. Python also makes integrating multiple systems very easy which makes it important part of top 5 technical skills for IT professionals.

Uses of Python

1) Can be used for web development
2) It can connect to data base for back-end processing
3) It can be used to handle big data

Advantages of Python

1) Easy syntax much like English language
2) Its lamda expression makes write complex programs using less lines of code compared to other languages
3) It runs on interpreter system which means that code can be executed as soon as it is written
4) Python can work on different platforms like Windows, Mac, Linux etc.

Environments for python programming

The following are the list of best IDE’s for Python Programming on Windows operating systems – PyCharm, Eclipse with Pydev, Wing IDE, Komodo IDE, Eric Python IDE, Sublime Text 3

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