Basic data terms

  • What are the basic concepts of data and information?

    Data is a collection of facts, while information puts those facts into context.
    While data is raw and unorganized, information is organized.
    Data points are individual and sometimes unrelated.
    Information maps out that data to provide a big-picture view of how it all fits together..

  • What are the basic terminologies used in statistics?

    Four big terms in statistics are population, sample, parameter, and statistic: A population is the entire group of individuals you want to study, and a sample is a subset of that group..

  • What are the terms of data analysis?

    Diagnostic Analysis, Predictive Analysis, Prescriptive Analysis, Text Analysis, and Statistical Analysis are the most commonly used data analytics types.
    Statistical analysis can be further broken down into Descriptive Analytics and Inferential Analysis..

  • What are the terms of data intelligence?

    The five major components of data driven intelligence are descriptive data, prescriptive data, diagnostic data, decisive data, and predictive data.
    These disciplines focus on understanding data, developing alternative knowledge, resolving issues, and analyzing historical data to predict future trends..

  • What are the terms used in database?

    The terms entity, attribute, table, primary key, foreign key, relational database, query, index, normalization, ACID properties, data warehousing, data mining, backup and recovery, data migration, and replication were all covered in detail in this article..

  • What is the basic term of data?

    Data: Fundamentally, data=information.
    We typically use the term to refer to numeric files that are created and organized for analysis.
    There are two types of data: aggregate and microdata.
    Aggregate data are statistical summaries of data, meaning that the data have been analyzed in some way..

  • What is the data in information terms?

    Data are the raw alphanumeric values obtained through different acquisition methods.
    Data in their simplest form consist of raw alphanumeric values.
    Information is created when data are processed, organized, or structured to provide context and meaning.
    Information is essentially processed data..

  • What is the term for data about the data?

    Data for processing has come to be complemented by metadata, sometimes referred to as "data about data," that helps administrators and users understand database and other data..

  • Why do we need to understand data?

    Data allows organizations to measure the effectiveness of a given strategy: When strategies are put into place to overcome a challenge, collecting data will allow you to determine how well your solution is performing, and whether or not your approach needs to be tweaked or changed over the long-term..

  • A data dictionary defines and describes technical data terms.
    Data terms could be database schemas, tables, or columns.
    It may include information about the data type, size, default values, constraints, relationships to other data, and the meaning or purpose of a given asset.
  • Data are the raw alphanumeric values obtained through different acquisition methods.
    Data in their simplest form consist of raw alphanumeric values.
    Information is created when data are processed, organized, or structured to provide context and meaning.
    Information is essentially processed data.
  • Data for processing has come to be complemented by metadata, sometimes referred to as "data about data," that helps administrators and users understand database and other data.
  • Diagnostic Analysis, Predictive Analysis, Prescriptive Analysis, Text Analysis, and Statistical Analysis are the most commonly used data analytics types.
    Statistical analysis can be further broken down into Descriptive Analytics and Inferential Analysis.
1. Data Engineering2. Data Governance3. Data Warehouse4. Data Fabric 
Aug 25, 2021101 Definitions of Common Data Terms17) Data Collaboration18) Data Democratization19) Data Enrichment20) Data Exchange21) Data 
Let's begin with the basics.
  • Data. This is information that has been converted into another form to be processed or analysed.
  • Big data. This refers to the vast amounts of structured and unstructured data that can come from a myriad of sources.
  • Open data.
  • Data warehouse.
  • Data mart.
  • Data mining.
  • Data centre.
  • Algorithm.
Demystifying the most used Data Science jargon in simple English. Ganes A Glossary of Big Data Terms. I. Data Engineering Terminology. 1. Data Engineering 

Data Architecture

Data architecture, also called data design, is the plan for an organization’s data management system. This can include all touchpoints in the data lifecycle, including how the data is gathered, organized, utilized, and discarded. Data architectsdesign the blueprints that organizations use for their data management systems.

Data Engineering

Data engineering is the process of making data accessible for analysis. Data engineersbuild systems that collect, manage, and convert raw data into usable information. Some common tasks include developing algorithms to transform data into a more useful form, building database pipeline architectures, and creating new data analysis tools.

What are the two types of data?

There are two types of data: ,aggregate and microdata

Data aggregation: ,a collection of datapoints and datasets

Data analytics: ,generally used to refer to the techniques and tools required to analyze massive amounts of data

Database: ,a collection of data organized for research and retrieval

What does data point mean?

Data point or datum: ,singular of data, generally refers to a single data value

Example: ,25,114 billion BTU of aviation gasoline was consumed by the transportation sector in the US in 2012

Dataset: ,a term used loosely to refer to a collection of related data items

This term is used very loosely

What is the difference between data and date?

Data are the actual values of the variable

They may be numbers or they may be words

Datum is a single value

Two words that come up often in statistics are mean and proportion

Basic data terms
Basic data terms

Linguistics book by Brent Berlin and Paul Kay

Basic Color Terms: Their Universality and Evolution is a book by Brent Berlin and Paul Kay.
Berlin and Kay's work proposed that the basic color terms in a culture, such as black, brown, or red, are predictable by the number of color terms the culture has.
All cultures have terms for black/dark and white/bright.
If a culture has three color terms, the third is red.
If a culture has four, it has either yellow or green.
Basic Color Terms: Their Universality and Evolution is a book

Basic Color Terms: Their Universality and Evolution is a book

Linguistics book by Brent Berlin and Paul Kay

Basic Color Terms: Their Universality and Evolution is a book by Brent Berlin and Paul Kay.
Berlin and Kay's work proposed that the basic color terms in a culture, such as black, brown, or red, are predictable by the number of color terms the culture has.
All cultures have terms for black/dark and white/bright.
If a culture has three color terms, the third is red.
If a culture has four, it has either yellow or green.

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