Types of Data - 'DVT'
Greetings everyone!
As a part of our "Data Visualization Techniques" course, Here is my article from a topic called - "Types of data".
In this module we are going to discuss about '6' data types namely:
As the name itself says, tabular data refers to the data that is displayed in columns or tables.
This data can be represented as a systematic presentation of data with the help of a statistical tale having a number of rows and columns and complete with reference number, title, reference number, title, description of rows and columns and also the foot notes, if any.
It will be organized in rows and columns. Rows represents observations and the columns represent attributes for those observations.
Basically, tree data is a non-linear data structure which has roots, branches, and also the leaves connected with one another.
As said it is a non-linear, it is also a hierarchal data structure.
It has the collection of nodes such that each node of a tree stores a value and a list of references to nodes. It does not store in a sequential manner.
Top most node is known as root node and the last is known as leaf node and it does not have children.
Graph data is also a non-linear data structure consisting of nodes & edges.
Here, nodes are also referred as vertices & edges are lines or arcs that connect any two edges in graph.
These are used to represent networks & are used to solve many real-time problems.
Text data type stores any type of text data.
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The actual text column type consists of four types- TINYTEXT, TEXT, MEDIUMTEXT and LONGTEXT.
All these types are very similar to each other yet, the only difference is the maximum amount of data each can store.
Out of these, smallest TEXT type, TINYTEXT shares the same character length as varchar. And these all values are treated as character strings.
It has the high-capacity character storage. This text family column is just like a varchar.
It cannot have default value.
Between our process and the external entities, there are data flows that show a brief description of the type of information exchanged between the entities and the system.
It is a is a managed service for "executing a wide variety of data processing patterns".
The 3 types of dataflow are:
Data can flow in different ways of data communication or transmission modes in networking. Those can be defined as one device to another or two devices can communicate in Simplex, Half-Duplex, or Full-Duplex.
Basically, it is a data that is recorded over consistent intervals of time.
Auto-Regressive Integrated Moving Average (ARIMA) models are among the most widely used time series forecasting techniques: In an Autoregressive model, the forecasts correspond to a linear combination of past values of the variable.
It is a sequence of data points collected over time intervals, allowing us to track changes over time. Time-series data can track changes over milliseconds, days, or even years.
Examples:
Financial markets, IoT and Sensor data, Application monitoring... etc.
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