Data Science with Cloud Computing
Sankhyana Consultancy Services Pvt. Ltd.
Data Driven Decision Science
What is Cloud Computing?
Cloud computing sanctions companies to access different computing accommodations like databases, servers, software, artificial perspicacity, data analytics, etc. over the cyber world, which is called the cloud in this case. These companies can run their applications on the best data centers in the world with minimal costs. This withal ascertains that minute companies or those in emerging economies can utilize this technology for zealous and intricate projects that would otherwise be quite costly. And this is veridical in the domain of Data Science as well. Cloud Computing has made Data Analytics and Data Management much simpler for Data Scientists.
Why is Cloud Computing Important in Data Science?
Let’s imagine for a second that there was no Cloud Computing for Data Science. Then companies would have to locally store data in servers and every time a Data Scientist needed to perform data analysis or extract some information from the data, they would require transferring the data to their system from the central servers and then perform the analysis. Can you imagine the complications in this?! This is not just remotely data as data analysis by companies utilizes an astronomically immense volume of data.
Moreover, it is very extravagant to engender servers for the data and while sizably voluminous companies can manage this facilely, it is very different for the more diminutive companies. These more minuscule companies cannot use servers as they require space to retain them. These servers require constant maintenance and upkeep and additionally require backups in case anything goes erroneous. Having servers additionally require immense orchestrating and it may additionally transpire that companies may obtain more or fewer servers than they require according to their data requisites. And this is where cloud computing comes in! Companies can utilize the cloud to host their data and they don’t need to worry about servers anymore as this is the headache of the cloud provider now! The companies can access server architecture in the cloud according to their desiderata and even preserve mazuma by only paying as much as the data they are utilizing on the cloud.
Cloud computing has democratized data in a manner that is unique in these times. Now, more diminutive companies can perform data analytics and compete with more sizably voluminous multinationals in the market without worrying about the non-compos mentis costs associated with Data Science. Data Science with Cloud Computing has become so popular now that it has given birth to Data as an Accommodation (DaaS).
Cloud Computing Platforms for Data Science
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1.???Google Cloud
The Google Cloud Platform is a cloud computing platform that is provided by Google. It provides the same infrastructure for companies that Google itself uses in its internal products such as Google Search, YouTube, Gmail, etc. Google Cloud provides sundry products for data analytics which include Big Query (Data warehouse), Dataflow (Streaming analytics), Dataproc (Running Apache Hadoop, Apache Spark clusters), Looker (Business Perspicacity Analytics), Google Data Studio (Visualization Dashboards, Data Reporting), Dataprep (Data Preparation), etc.
2.???Microsoft Azure
Microsoft Azure is a cloud computing platform engendered by Microsoft. It was initially relinquished in 2010 and is a popular cloud computing platform for data science and data analytics. Some of the Microsoft Azure products for data analytics are Azure Synapse Analytics (Data Analytics), Azure Stream Analytics (Streaming analytics), Azure Databricks (Apache Spark analytics), and Azure Data Lake Storage (Data Lake), Data Factory (Hybrid data integration), etc. Microsoft Azure withal has support for databases including Azure Cosmos DB (NoSQL database), Azure SQL Database (SQL database), etc.
3.???Amazon Web Services
Amazon Web Accommodations is a cloud computing platform that is a subsidiary of Amazon. It was launched in 2006 and is currently one of the most popular cloud computing platforms for data science. AWS provides sundry products for data analytics which include Amazon QuickSight (business analytics accommodation), Amazon RedShift (data warehousing), AWS Data Pipeline, AWS Data Exchange, Amazon Kinesis (genuine-time data analysis), Amazon EMR (Immensely colossal data processing), etc. Amazon Web Accommodations withal provides products for databases which include the Amazon Aurora (relational database) and Amazon DynamoDB (NoSQL database). Some of the more popular companies that use AWS include Netflix, NASA, etc.
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