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Data Analytics Tools of 2020

Andrew Duch — Fri, 13 Nov 2020 13:41:35 +0000

What are Data Analytics tools used for?

These days business decisions made are not at all based on the intuitions of people in charge; rather, it is driven by data. Analyzing data gives insights into the exact problems faced and helps clear the roadblocks toward increased revenue and customer experience. A variety of Data Analytics tools and techniques help in achieving this. The most important ones are listed here in this blog.

Tools for Data Analysis

R Programming

R is one of the best Data Analytics tools used for data mining, modeling, and heavy statistical computing. This free, open-source software is not just employed in analyzing data, but also creates software and applications that can perform statistical analysis seamlessly.

Additionally, R has a graphical interface, making it a viable choice while carrying out a wide range of analytical modeling, such as time series analysis, linear/non-linear modeling, and data clustering, among others. Most statisticians use this because of the ready-to-publish nature of its plots, graphs, equations, and formulae.

The language can come off as slightly complex compared to other Data Analytics tools, but it still remains one of the most favored.

Python

This high-level language supports both object-oriented programming and structured programming. Despite being a high-level language, it is easiest to learn in the IT world.

Python is a good facilitator in data analysis. Let us see how:

It provides libraries like NumPy and Panda, making it easier to process data with parallel processing.
Not always you get data in readily usable formats. Python uses libraries like BeautifulSoup and Scrapy to extract it from the Internet.
Visualizing datasets makes analysis much easier than trying to figure out patterns by just staring at them. Matplotlib and Seaborn are some libraries that help you represent data in the form of pie charts, bar graphs, etc.
Its capacity to compute incredibly complex mathematical problems makes it the go-to tool for Machine Learning enthusiasts. Scikit-Learn helps them do such complex operations.
Python also processes images using the OpenCV library.

Interested in learning these tools, then join our data analytics courses in Bangalore with placement to get clear-cut knowledge that uplifts your career as a Data Analyst.

SAS

Statistical Analysis System (SAS) finds its application increasingly in Machine Learning, Data Science, and Business Intelligence (BI) problems. It is among the most popular BI tools that come with various features, including data visualization, data exploration, creating easy and insightful analysis, interactive dashboards, and ad-hoc reporting.

SAS is one of the most frequently used statistical tools for data analysis. Some important features of SAS are as follows:

The iOS and Android-friendly BI companion app helps you easily monitor business anywhere, at any time.
SAS BI can be easily accessed through Microsoft Office, where analysts can create and distribute reports and charts as per convenience.
SAS can predict behaviors and manage and optimize their communications.

Apache Spark

This University of California developed tool is a large-scale data processing engine, which executes applications in Hadoop. It is known for its speed in processing, where the applications are executed 100x faster in memory and 10x faster on disk than Hadoop.

Because Apache Spark can work with Big Data efficiently, a lot of big companies with large amounts of unstructured data are adopting it into their stack.

It can support basic data loading to handling SQL queries and Machine Learning.
It has a unified nature that allows it to combine different libraries and processing types.
It loads data from storage systems and performs computation operations on them.
Spark is associated with a wide range of functionality. It includes libraries for structured data and SQL, stream processing, Machine Learning, and graph analytics.
Now, let us read about Excel BI tools which are also one of the top Data Analytics tools used in industries today.

Microsoft Excel
Analyzing data has become the most powerful skill these days. MS Excel might be the most primitive tools used among Data Analysts, but it makes the go-to option of any beginner in the field.

Even if you are an expert in all of the above tools, you might still need to use Excel. It is the most basic and popular tool used in the industry.
It makes use of pivot tables to filter complex data and draws insights from them as per client requirements.
It has advanced analytics options that help in modeling capabilities.

Microsoft to developers: These are our biggest and best open-source projects

Andrew Duch — Fri, 14 Aug 2020 08:32:26 +0000

Microsoft, under CEO Satya Nadella, has said and done a lot to shed its image as a pariah of Linux and open-source software communities.

With a Linux kernel for Windows 10, GitHub, a new Android Surface Duo, and the commercial cloud as its main source of revenue, Microsoft is a very different company than it was 30 years ago when it was afraid open-source software would gobble up its intellectual property and revenues.

Nowadays, it's got a growing number of open-source projects, including its hugely popular cross-platform code editor Visual Studio Code (VS Code), .NET Core, the hit JavaScript-based programming language TypeScript, and new open-source Windows developers tools like PowerToys and Windows Terminal.

Microsoft has now launched a website – of course, built on open-source technologies – to showcase how it's embracing open source to "bring choice, technology and community to our customers".

According to the company, over 35,000 engineers at the company are using GitHub Enterprise Cloud to host and release official Microsoft open-source projects, samples, and documentation.

The site also details the influence the One Engineering System (1ES) team has on the Microsoft open-source program. 1ES, a team of around 200 people, aims to improve Microsoft's own engineering processes and then bring these tools and processes to customers, such as the Git Virtual File System (GVFS).

Jeff Wilcox, a software engineer with the Microsoft Open Source Programs Office, announced the new site today. He notes that it is "built by the Ruby open-source project Jekyll (that also powers GitHub Pages)".

Wilcox reckons the site provides "a nearly real-time view of things happening across our projects on GitHub".

It's of course hosted in the Azure cloud and makes use of Microsoft's own Azure Front Door service for managing containers in the Azure Kubernetes Services, as well as TypeScript and Node.js. Know more about Azure from the best Azure course in Hyderabad.

Among the main open-source projects from Microsoft include Windows Terminal, VS Code, .NET MAUI, the Windows Calculator, TypeScript, the Cascadia Code font, the Windows package manager Winget, PowerShell, and the source code for the Linux kernel used in Windows Subsystem for Linux 2.

The site also highlights Microsoft's Free and Open Source Software Fund (FOSS Fund), which allows Microsoft employees to "collectively select open-source projects to receive $10,000 sponsorship awards throughout the year."

"Microsoft's engineers select projects they are super passionate about. Only employees who contribute to open-source projects can participate in the selection process," Microsoft states.

Last week, Google showed off its contributions to open-source software, revealing that around 12,500 Google employees contribute to public code repositories.

In 2019 Google employees created over 570,000 issues, opened over 150,000 pull requests, and created more than 36,000 push events on GitHub.

Microsoft argued at the time it acquired GitHub in 2018 that it was the most active organization on the hosting and development service because its employees had made two million commits, or updates, to open-source projects in a year.

How To Prepare For Azure Cloud Certification?

Andrew Duch — Sat, 08 Aug 2020 06:32:33 +0000

Microsoft Azure is one of the top cloud platforms and it is important for IT professionals to learn Azure to enhance their job skills. Given so many enterprises are running or Azure, specific certifications can be valuable for cloud experts.

Holding an Azure certification gives people an advantage to land a well-paying job role of their choice, and get recognized as a cloud computing expert. A certification can really add a lot to your career as a cloud computing expert, but it’s also one of the toughest certifications to acquire as well. Azure has a constantly expanding set of certifications for different cloud services.

There are specific examinations that candidates can take to get the certifications directly from Microsoft. Here is the link to the certifications and the details to get an idea of how people prepare for taking these Azure certifications. These exams have moderate to a very high level of difficulty and require students to prepare thoroughly.

Many of the certifications are based on specific roles and tasks related to Azure tools and cloud services. Some of the certifications include Azure Fundamentals, Microsoft Certified: Azure Administrator Associate (AZ:104), Microsoft Certified Azure Developer Associate (AZ:204), Microsoft Azure Architect Technologies (AZ:30), Microsoft Azure Architect Design (AZ-301) and more. Different exams check specific expertise related to cloud management and security for granting the certifications.

The first step is to look at the basic concepts of the Azure cloud and the various services. One of the most important things is that learners should have a basic understanding of cloud computing, virtual machines, networking storage, and other infrastructure-related topics.

Practical Knowledge

There’s nothing better than practical knowledge. The exam involves practical tests and therefore hands-on practice related to Azure products is very necessary. This is because the nature of your certifications is to leverage the cloud platform. So, students should acquire practical knowledge not just theoretical know-how. This is why some people say IT experts and cloud admins can leverage their already existing hands-on skills to prepare Azure certification exams from the Azure Online Training program. Learners can acquire a free Azure account to gain Azure cloud services for a specific time to build up some practical knowledge.

There are also classroom training programs provided by training institutes where candidates can attain proper training with a trustworthy Azure training service provider. At the same time, aspirants can take practice tests to check which areas they have weaknesses. There, learners can learn how to work with Cloud APIs as well as deploy SaaS, PaaS and IaaS cloud services.

The Learning Process

Coming to learning material, there are both free and paid resources that students can access to learn about these topics. There are courses available on platforms like Udemy where aspirants can seek expertise on concepts like Powershell, storage, app service, SQL database, etc.

Aspirants can also go through several blogs that are written on various cloud topics, which can help them prepare for the certifications. There are self-learning courses that can be utilized as well for learning, including videos and PowerPoint presentations. Learners can also take mock and practice tests.

Aspirants can join special training programs provided by many private institutes on Azure training. Specific certifications require special expertise in particular domains related to certain job roles when it comes to using extensive cloud platforms. Understanding the fundamentals is one of the most critical things when it comes to seeking certification concepts like cloud computing. Certification aspirants can also solve previous years questions exam papers to get a thorough understanding.

A deep dive into specific technology topics can be made using course material, books, documentation blogs. Also, learners can check official resources provided by Microsoft on their website. Besides, you can also join social media communities and different platforms to discuss how candidates can prepare.

What is Cloud Computing

Andrew Duch — Mon, 02 Mar 2020 07:16:01 +0000

Cloud computing is a process of utilizing a network server for performing operations like storing accessing processing of data from or to a database rather than using a local server or computer data. The word “cloud” itself refers to the establishment of servers across the internet for access.

What is cloud computing:

Establishment of a virtual data and usage of its access for our purposes without any actual physical components. Cloud computing is purely based on the sharing of resources for our performances. These resources are can be accessed virtually by communication of servers.

Types of Cloud Computing:

Public Cloud - A cloud provider owns and manages all the hardware, software and supporting infrastructure provided to access them and manage accounts using a web browser. Microsoft Azure is one of the examples of the public cloud. The Azure tutorial gives a brief explanation. As it is operated by third-party cloud service providers to deliver resources such as services and storage through the Internet.

Private Cloud -This is a cloud that mainly consists of a private network. Even if it asks for the third-party to involve in its resources only through the private network of the organization it is possible to access the servers and storage devices. These cloud computing resources are exclusively used by a single organization.

Hybrid cloud -This cloud is a combination of both public and private clouds. It allows the data and application to pass through the public cloud and private cloud.

Satya Nadella on Cloud Computing

Microsoft Corp. chief executive Satya Nadella on Tuesday indicated his company is betting big on cloud and artificial intelligence (AI), or ‘intelligent cloud’, in India.

Microsoft intends to make its cloud computing platform Azure “the world’s computer", Nadella said at the Future Decoded summit in Bengaluru. Microsoft Azure has 57 data centre regions globally, with three centres in Pune, Chennai and Mumbai.