It is the study of data to extract meaningful insights for business.

It is a multidisciplinary approach that combines principles and practices from the fields of mathematics, statistics, artificial intelligence, and computer engineering to analyze large amounts of data.

refers to the practice or science of collecting and analyzing numerical data in large quantities, especially for the purpose of inferring proportions in a whole from those in a representative sample.

refers to the simulation or approximation of human intelligence in machines. The goals of artificial intelligence include computer-enhanced learning, reasoning, and perception.

an umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive, and instead the problems are solved by helping machines "discover" their "own" algorithms, without needing to be explicitly told what to do by any human-developed algorithms.

a software application or web interface that aims to mimic human conversation through text or voice interactions.

a finite sequence of rigorous instructions, typically used to solve a class of specific problems or to perform a computation. These are used as specifications for performing calculations and data processing.

is a robot system used for manufacturing. These are automated, programmable and capable of movement on three or more axes.

an interdisciplinary subfield of computer science and linguistics. It is primarily concerned with giving computers the ability to support and manipulate speech.

generally self-employed and provides professional administrative, technical, or creative assistance to clients remotely from a home office.

the process of acquiring new understanding, knowledge, behaviors, skills, values, attitudes, and preferences. The ability to learn is possessed by humans, animals, and some machines; there is also evidence for some kind of learning in certain plants.

tasks include methods for acquiring, processing, analyzing and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, e.g.

a field of study that focuses on the process of monitoring and controlling the movement of a craft or vehicle from one place to another.

What is happening in the business?

Why did something happen?

What is likely to happen next?

What do I need to do next?

-Understanding the problem -Asking the right questions -Looking for the right data to solve the problem -Gather the data

-choosing what model to use -what algorithm to use to solve the problem

results are presented and communicated

-raw data is to be manipulated -data munching is done -data format is formed

-implementation and execution of the model -putting the data for analysis

the process of examining and interpreting data to extract valuable insights and make informed decisions. It involves the use of various techniques, tools, and technologies to analyze and manipulate data in order to discover patterns, trends, correlations, and other useful information.

the most basic form of data analysis. It involves summarizing historical data to provide a clear picture of past events and trends.

This type of analytics helps in understanding what has happened, often through visualization techniques such as charts, graphs, and dashboards. It is useful for reporting and providing context.

a step further by examining historical data to understand why certain events or trends occurred.

This type of analysis is valuable for troubleshooting problems and optimizing processes.

uses historical data and statistical algorithms to forecast future outcomes or trends. It helps organizations make informed decisions by providing insights into potential future scenarios.

Common applications include sales forecasting, demand prediction, and risk assessment.

builds upon predictive analytics and suggests a course of action to achieve a desired outcome. It not only predicts future events but also provides recommendations for making the best decisions to optimize results.

used in areas like supply chain optimization, healthcare treatment planning, and financial portfolio management.

an open-ended approach used to investigate data for patterns and relationships. It is often used when the dataset is large or complex and the goal is to gain initial insights.

Visualization tools and statistical techniques are commonly used in this analytics to uncover hidden patterns and anomalies.

focuses on analyzing unstructured text data, such as customer reviews, social media posts, emails, and documents.

Natural language processing (NLP) techniques are used to extract insights from text, including sentiment analysis, topic modeling, and information extraction.

deals with geographic or location-based data. It involves analyzing data that has a spatial component, such as maps, GPS coordinates, and geographic information systems (GIS).

is used in urban planning, environmental monitoring, and location-based marketing

processes and analyzes data in real-time as it is generated. This is crucial for applications like fraud detection, IoT (Internet of Things) data analysis, and monitoring network performance.

It helps businesses understand customer sentiment, track brand mentions, and assess the impact of social media campaigns.

involves the analysis of website and online user behavior data. It helps website owners optimize their web presence by understanding user interactions, traffic sources, and conversion rates.

the fundamental building block upon which all analysis and insights are based. Understanding data, its sources, and its types is crucial for any data science practitioner.

refers to raw facts, information, or observations that are typically collected and stored in a structured or unstructured format. It can come in various forms, and it is the primary input for any data analysis process.

lacks a specific structure and includes text, images, videos, and more.

With the advent of technology and the internet, organizations now have access to vast amounts of data

organized and follows a predefined format, often stored in databases or spreadsheets.

characterized by its volume, velocity, variety, and veracity. Managing and analyzing this require specialized tools and techniques.

This is crucial for accurate analysis. Data may contain errors, duplicates, or inconsistencies, which can lead to incorrect conclusions.

these are essential steps in data preparation.

Data obtained from sources outside the organization, including publicly available data, market research reports, government datasets, and social media data.

Data generated and collected within an organization, such as sales records, customer data, employee information, and transaction logs.

In the context of IoT (Internet of Things), data from sensors and devices, such as temperature sensors, GPS devices, and wearable fitness trackers, can provide valuable insights.

involves extracting data from websites and online sources. It is commonly used to gather data for text analytics, price monitoring, and competitive analysis

Organizations often collect data through these to gather feedback, preferences, and opinions from customers or respondents.

these platforms generate vast amounts of user-generated content that can be analyzed for sentiment analysis, trend identification, and customer insights.

Data generated by automated processes, such as log files, system metrics, and event logs, is used for monitoring and troubleshooting.

consists of numbers

Data that can take any value within a range, such as temperature or age.

includes unstructured textual information and is commonly analyzed using natural language processing (NLP) techniques for sentiment analysis, topic modeling, and text classification

represents categories or labels and is often used to group data into distinct classes, such as colors, product categories, or customer segments.

Data that can only take specific, distinct values, such as the number of employees or items sold.

it is collected at regular time intervals and is used to analyze trends and patterns over time, such as stock prices, weather data, or website traffic

consists of only two possible values, often represented as 0 and 1, and is used in various contexts, including machine learning classification problems.

includes information with a geographic or spatial component, such as latitude and longitude coordinates or GIS (Geographic Information System) data.

It has a user-friendly interface with various elements and functionalities that enable users to work with spreadsheets, perform calculations, create charts, and analyze data.

is located at the top of the Excel window and consists of tabs, each containing groups of related commands.

It provides access to most of Excel's features and functionalities, organized into categories like "Home," "Insert," "Page Layout," "Formulas," "Data," "Review," and "View."

is located above the Ribbon and provides quick access to frequently used commands.

Users can customize this toolbar by adding their preferred commands.

the main Excel file that contains one or more worksheets

it is also called spreadsheet

Each of this is displayed in a separate tab at the bottom of the Excel window.

grid of rows and columns where users enter, manipulate, and analyze data.

Each of this can contain text, numbers, formulas, and charts. Users can have multiple worksheets within a single workbook.

run horizontally from left to right and are numbered numerically (1, 2, 3, ...).

run vertically from top to bottom and are labeled alphabetically (A, B, C, ...).

The intersection of a row and a column is called a ___ and each this is identified by a unique ____ reference (e.g., A1, B2).

a fundamental unit in Excel where data can be entered. Users can input text, numbers, dates, and formulas into this

a fundamental unit in Excel where data can be entered. Users can input text, numbers, dates, and formulas into this.

The active cell is outlined, and its address is displayed in the ____ (located to the left of the Formula Bar).

displays the content of the active cell, whether it's data, a formula, or a function. Users can edit cell contents directly from this.

it displays the cell reference or name of the active cell. Users can also use it to quickly navigate to specific cells by entering cell references.

start with an equal sign (=) and can include mathematical operators and cell references (e.g., "=A1+B2").

are predefined operations (e.g., SUM, AVERAGE) that can be used for calculations.

is a small square in the lower-right corner of the active cell. It can be used to quickly fill adjacent cells with a series of values or to copy and autofill formulas.

can be inserted and customized from the "Insert" tab.

thistab allows users to set up page orientation, page size, margins, and headers/footers for printing worksheets.

this tab offers features for sorting, filtering, and managing data. It also includes tools for data validation, data import/export, and text-to-columns transformations.

contains tools for spell-checking, tracking changes, adding comments, and protecting worksheets and workbooks.

tab provides options for changing the view of the spreadsheet, including Normal, Page Layout, and Page Break Preview. It also allows users to split the worksheet into panes for easier navigation.