•Government publications (e.g. social trends)
•Local libraries and local government offices (e.g. census)
•Trade organisations
•Market intelligence reports
•Newspaper reports and specialist publications
•Internal company records
•The internet
Data can come from various sources such as surveys, sensors, social media, transactions, and research studies. It can be collected intentionally through structured methods or generated as a byproduct of digital activities. Once collected, data can be stored and processed for analysis to derive insights and make informed decisions.
An external source of data is a connection to an external data base and contains data that does not change much. The difference of internal source of data is data that can change because it comes from sources inside an organization including inventory transactions, purchase orders, and sales.
Structured data is organized and has a defined format, making it easy to store and retrieve. Unstructured data, on the other hand, lacks a predefined structure and may come in various formats like text, images, or videos. Structured data is often stored in databases and can be easily analyzed using traditional methods, while unstructured data requires special techniques like natural language processing to extract meaningful insights.
A data dictionary is a repository that contains definitions of data processes, data flows, data stores, and data elements used in an organization. It helps to provide a common understanding of data terminologies and structures within a dataset or system. Data dictionaries are often used to maintain consistency and clarity in data management and analysis processes.
Metadata is data about data that provides information such as the structure, format, and characteristics of the data stored in a data warehouse. It is used in data warehouse architecture to facilitate data integration, data governance, and data lineage. Metadata helps users understand and manage the data in the data warehouse efficiently.
Explicit data is data that is clearly stated or defined, while implicit data is implied or hinted at. Explicit data is typically straightforward and directly provided, whereas implicit data requires context or interpretation to understand its meaning. In the context of programming, explicit data is data that is clearly declared and specified, while implicit data is data that is inferred or derived.
It is a way for data to be separated, using a punctuation mark, most commonly commas. It can be a way for data to come from a different format and then be split into cells and/or columns.It is a way for data to be separated, using a punctuation mark, most commonly commas. It can be a way for data to come from a different format and then be split into cells and/or columns.It is a way for data to be separated, using a punctuation mark, most commonly commas. It can be a way for data to come from a different format and then be split into cells and/or columns.It is a way for data to be separated, using a punctuation mark, most commonly commas. It can be a way for data to come from a different format and then be split into cells and/or columns.It is a way for data to be separated, using a punctuation mark, most commonly commas. It can be a way for data to come from a different format and then be split into cells and/or columns.It is a way for data to be separated, using a punctuation mark, most commonly commas. It can be a way for data to come from a different format and then be split into cells and/or columns.It is a way for data to be separated, using a punctuation mark, most commonly commas. It can be a way for data to come from a different format and then be split into cells and/or columns.It is a way for data to be separated, using a punctuation mark, most commonly commas. It can be a way for data to come from a different format and then be split into cells and/or columns.It is a way for data to be separated, using a punctuation mark, most commonly commas. It can be a way for data to come from a different format and then be split into cells and/or columns.It is a way for data to be separated, using a punctuation mark, most commonly commas. It can be a way for data to come from a different format and then be split into cells and/or columns.It is a way for data to be separated, using a punctuation mark, most commonly commas. It can be a way for data to come from a different format and then be split into cells and/or columns.
when did data bases first come into use
A hypothesis comes before data. A hypothesis is an estimated guess to what will happen. And Data is the steps it takes to come to a solution in a problem.
There would be some. For example if you copy data from Excel into Word, only values will come through, not the underlying formulas.There would be some. For example if you copy data from Excel into Word, only values will come through, not the underlying formulas.There would be some. For example if you copy data from Excel into Word, only values will come through, not the underlying formulas.There would be some. For example if you copy data from Excel into Word, only values will come through, not the underlying formulas.There would be some. For example if you copy data from Excel into Word, only values will come through, not the underlying formulas.There would be some. For example if you copy data from Excel into Word, only values will come through, not the underlying formulas.There would be some. For example if you copy data from Excel into Word, only values will come through, not the underlying formulas.There would be some. For example if you copy data from Excel into Word, only values will come through, not the underlying formulas.There would be some. For example if you copy data from Excel into Word, only values will come through, not the underlying formulas.There would be some. For example if you copy data from Excel into Word, only values will come through, not the underlying formulas.There would be some. For example if you copy data from Excel into Word, only values will come through, not the underlying formulas.
usally by clicking on the data you wish to format an option will come up asking you if you want to format it
Yes. The order is question, hypothesis, lab, organize data, communicate results
12 centuary old english
Yes data virtualization is a real term. Data virtualization is used by companies to predict where the traffic will come from. It helps companies to see where the consumers are.
with data redundancy there willbe more wastage of memory space as same type of data willbe saved many times when to want to see the data all duplicate results will come
Using data from a number of sources to come to a conclusion
come up with new hypothesis
scientists can come to different conclusions based off the same data