SPARK DATABOX

Best Online Software Training Institute

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Why SPARK DATABOX

People are at the heart of customer success and with training and certification through Spark Databox, you will learn to master data analytics from the team that started the Spark research project

BIGDATA TRAINING

What is big data? It’s a phrase used to quantify data sets that are so large and complex that they become difficult to exchange, secure, and analyze with typical tools.

These courses on big data show you how to solve these problems, and many more, with leading IT tools and techniques.

Big data is a field that treats ways to analyze, systematically extract information from, or otherwise, deal with data sets that are too large or complex to be dealt with by traditional data-processing application software
Data with many cases (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate.

Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy, and data source.

AWS TRAINING

Amazon Web Services (AWS) is a subsidiary of Amazon that provides on-demand cloud computing platforms and APIs to individuals, companies, and governments, on a metered pay-as-you-go basis.

In aggregate, these cloud computing web services provide a set of primitive abstract technical infrastructure and distributed computing building blocks and tools. One of these services is Amazon Elastic Compute Cloud (EC2), which allows users to have at their disposal a virtual cluster of computers, available all the time, through the Internet.

AWS’s version of virtual computers emulates most of the attributes of a real computer, including hardware central processing units (CPUs) and graphics processing units (GPUs) for processing; local/RAM memory; hard-disk/SSD storage; a choice of operating systems; networking; and pre-loaded application software such as web servers, databases, and customer relationship management (CRM).

DEVOPS TRAINING

DevOps is a set of practices that combines software development (Dev) and IT operations (Ops). It aims to shorten the systems development life cycle and provide continuous delivery with high software quality.

DevOps improves collaboration and productivity by automating infrastructure and workflows and continuously measuring applications performance. In this course, you will learn about Version Controlling, Code Automation, Continuous Integration, Continuous Deployment, Configuration Management, and Monitoring of application.

  DevOps is the combination of cultural philosophies, practices, and tools that increases an organization’s ability to deliver applications and services at high velocity: evolving and improving products at a faster pace than organizations using traditional software development and infrastructure management processes. This speed enables organizations to better serve their customers and compete more effectively in the market.

Under a DevOps model, development and operations teams are no longer “siloed.” Sometimes, these two teams are merged into a single team where the engineers work across the entire application lifecycle, from development and test to deployment to operations, and develop a range of skills not limited to a single function.

DATA SCIENCE TRAINING

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from many structural and unstructured data.

Data science is related to data mining, deep learning, and big data.
Data science is a “concept to unify statistics, data analysis, machine learning, domain knowledge, and their related methods” in order to “understand and analyze actual phenomena” with data.

It uses techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, domain knowledge, and information science.

Turing award winner Jim Gray imagined data science as a “fourth paradigm” of science (empirical, theoretical, computational, and now data-driven) and asserted that “everything about science is changing because of the impact of information technology” and the data deluge.

RPA TRAINING

Robotic process automation (or RPA) is a form of business process automation technology based on metaphorical software robots (bots) or on artificial intelligence (AI)/digital workers.

It is sometimes referred to as software robotics (not to be confused with robot software).
In traditional workflow automation tools, a software developer produces a list of actions to automate a task and interface to the back-end system using internal application programming interfaces (APIs) or dedicated scripting language.

In contrast,
RPA systems develop the action list by watching the user perform that task in the application’s graphical user interface (GUI) and then perform the automation by repeating those tasks directly in the GUI.

RPA tools have strong technical similarities to graphical user interface testing tools.

These tools also automate interactions with the GUI and often do so by repeating a set of demonstration actions performed by a user. RPA tools differ from such systems that allow data to be handled in and between multiple applications, for instance, receiving the email containing an invoice, extracting the data, and then typing that into a bookkeeping system.

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