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- is a method of plotting numeric data. It is similar to a box plot, with the addition of a rotated kernel density plot on each side. Violin plots are similar to box plots, except that they also show the probability density of the data at different values, usually smoothed by a kernel density estimator. Violin plots are used when you want to observe the distribution of numeric data, and are especially useful when you want to make a comparison of distributions between multiple groups. The peaks, valleys, and tails of each group’s density curve can be compared to see where groups are similar or different. Additional elements, like box plot quartiles, are often added to a violin plot to provide additional ways of comparing groups, and will be discussed below.

-is defined as a graphical method of displaying variation in a set of data. In most cases, a histogram analysis provides a sufficient display, but a whisker plot can provide additional detail while allowing multiple sets of data to be displayed in the same graph.whisker plots are very effective and easy to read, as they can summarize data from multiple sources and display the results in a single graph. Whisker plots allow for comparison of data from different categories for easier, more effective decision-making. You can use whisker plots when you have multiple data sets from independent sources that are related to each other in some way. Examples include:
- Test scores between schools or classrooms
- Data from before and after a process change
- Similar features on one part, such as camshaft lobes
- Data from duplicate machines manufacturing the same products

- is a graph that gives you a good indication of how the values in the data are spread out. Although box plots may seem primitive in comparison to a histogram or density plot, they have the advantage of taking up less space, which is useful when comparing distributions between many groups or datasets. Box plots divide the data into sections that each contain approximately 25% of the data in that set. Box plots are useful as they provide a visual summary of the data enabling researchers to quickly identify mean values, the dispersion of the data set, and signs of skewness.

The image above is a boxplot. A boxplot is a standardized way of displaying the distribution of data based on a five number summary (“minimum”, first quartile (Q1), median, third quartile (Q3), and “maximum”). It can tell you about your outliers and what their values are. Outliers are data points that differ significantly from other observations. It can also tell you if your data is symmetrical, how tightly your data is grouped, and if and how your data is skewed.

Correlation is measure of dependencies between two numerical features. We can interpret it like how change second feature if first one increase/deacrese on 1 unit. Correlation takes values from range [-1, 1]:
Value 1 means strongly positive correlation
Value 0 means lack of dependency between two features
Value -1 means negative correlation.

- The bar plot is another univariate plot on a two-dimensional axis. The two axes are not called x- or y-axes. Instead, one axis is called the category axis showing the category name, while the other, the value axis, shows the numeric value of that category, given by the length of the bar. Barplot is sometimes described as a boring way to visualize information, but from another point of view it's incredible efficiency. There are a few variations that allow one to create more eye-catching figures without losing any of the barplot accuracy.

is a framework implementation of a software bus using stream-processing. It is an open-source software platform developed by the Apache Software Foundation written in Scala and Java. The project aims to provide a unified, high-throughput, low-latency platform for handling real-time data feeds. Kafka supports many of today's best industrial applications. We will provide a very brief overview of some of the most notable applications:
Twitter is an online social networking service that provides a platform to send and receive user tweets. Registered users can read and post tweets, but unregistered users can only read tweets. Twitter uses Storm-Kafka as a part of their stream processing infrastructure.
Apache Kafka is used at LinkedIn for activity stream data and operational metrics. Kafka mes-saging system helps LinkedIn with various products like LinkedIn Newsfeed, LinkedIn Today for online message consumption and in addition to offline analytics systems like Hadoop. Kafka’s strong durability is also one of the key factors in connection with LinkedIn.
Netflix is an American multinational provider of on-demand Internet streaming media. Netflix uses Kafka for real-time monitoring and event processing.
Mozilla is a free-software community, created in 1998 by members of Netscape. Kafka will soon be replacing a part of Mozilla's current production system to collect performance and usage data from the end-user’s browser for projects like Telemetry, Test Pilot, etc.
Oracle provides native connectivity to Kafka from its Enterprise Service Bus product called OSB (Oracle Service Bus) which allows developers to leverage OSB built-in mediation capabilities to implement staged data pipelines.

- acronym from “Scalable Language”, is a strong statically typed general-purpose programming language which supports both object-oriented programming and functional programming. Scala runs on the Java platform (Java virtual machine) and is compatible with existing Java programs. Scala is currently one of the most popular programming languages, with a high demand amongst software development companies, globally. It’s functional & object oriented dual nature, static typing, high expressiveness & JVM integration makes it a perfect choice for many companies, like Twitter, LinkedIn, Infor, Netflix & Amazon, These companies use Scala to create web portals, big data applications, games & code-generators.

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- is a distributed, fault-tolerant data warehouse system that enables analytics at a massive scale. A data warehouse provides a central store of information that can easily be analyzed to make informed, data driven decisions. Hive allows users to read, write, and manage petabytes of data using SQL.Hive is built on top of Apache Hadoop, which is an open-source framework used to efficiently store and process large datasets. As a result, Hive is closely integrated with Hadoop, and is designed to work quickly on petabytes of data. What makes Hive unique is the ability to query large datasets, leveraging Apache Tez or MapReduce, with a SQL-like interface.