The programming languages that are important in data analytics

 The technology that has become quite the uproar in industries today is data science. People are sought after in order to perform data analytics and those who have skill in this field with programming knowledge are valuable throughout industries and organizations. Learning programming languages is very important for data analytics. 

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Python

• An easy language which is interpreter based and can be used for programming of a high-level. It is a very versatile language that has a huge library and hence can take up multiple roles. 

• You will hear a lot of this going on today because it has become extremely popular in the field of data science because of how easy it is to learn compared to other existing languages.

• The codes are readable and tackling problems that are complex gets easier if you use a language that is easy to understand. 

R

• This is the go-to language for statistical tasks because it is a language that is meant for statistical analysis and is popular in this segment. 

• But remember, this is only meant for statistical programming and hence, may not be a viable choice for general tasks that do not fall under this category.

SQL

• Data analysts are urged to learn this compulsorily because this is what you will use in order to retrieve data that come from organized data sources. 

• Databases can be manipulated, queried and updated using this language and it has a specific role which is crucial for data analysts. 

Scala

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• Scala can be treated as the sister of Java, which is also a programming language. It can be considered a functional as well as an object-oriented programming language. They are similar but not the same in usage.

• Large amounts of data can easily be dealt with using this programming language. 

• This is a language used for handling large amounts of data because it is scalable. 

• It can be easily paired with other tools to process data parallelly in the case that the requirement asks for it. 

Julia

• A program meant for scientific computing; it is another simple programming language. 

• The performance of it is known to be very swift. 

• Ideal for places that need complex mathematical operations to be taken care of. 

• Complex problems are solved in lightning-fast speed using this language.

SAS

• Used mostly for statistical analysis. Similar to R but it is not an open-source. 

• This language is one of the oldest ones designed for the purpose of statistics. 

• Can be used for predictive modelling, business intelligence and advanced analytics.

• Machine learning and a good range of libraries is offered by SAS.

Java

• This language can be used for general purposes because it's a language which is object-oriented. 

• It is a versatile language and has been embedded in electronics like desktop applications and other web applications. 

• This language helps in managing data, the process and storing of such big data as well. 

• The number of tasks it can handle at once is limitless given the potential of Java.

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Hundreds of programming languages are used and taught today. So, narrowing down your choices in terms of what to learn can be a task. You will need to know how to play your strengths and pick what will enhance your skills, something Data analytics course Pune can help you figure out.

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