What is Data in Computing?
Data is information that can be interpreted and used by computers. It is a collection of facts, such as numbers, words, measurements, observations or even just descriptions of things. In computing, data is typically stored electronically in the form of files or databases. Data can come from many sources including user input (typed words or images), sensors (temperature readings.) or algorithms (calculations).
How do computers use Data?
Computer systems use data to process tasks ranging from sending emails to performing complex calculations. Without data, they won’t work. The data fed into a computer system dictates the instructions it will receive and therefore the actions it will take. For example, when you enter a web address into your browser, this data tells the computer to fetch the relevant web page from a server and display it on your screen.
What types of Data does a computer understand?
Computers only understand two types of data; binary code and character-based code. Binary code consists only of ones and zeros—which can be meaningful when put together in long, differentiated strings. Character-based code consists of letters, numbers, and symbols that humans recognize as part of an alphabet, such as ASCII for English characters or Unicode for languages like Arabic.
Why is Data compression important when storing computer files?
Data compression reduces the size of digital files by encoding them in fewer bits than normal. By reducing file sizes, we can store more information in limited storage space, transfer files across networks faster and transmit data over mobile networks with better efficiency. Two popular methods for compressing digital files are lossless compression (where no quality is lost but efficiency gains are minimal), or lossy compression (where some detail may be lost but further size reductions are possible).
How is Data secured on computers?
Data security ensures that sensitive information cannot fall into the wrong hands. Techniques used to secure computer data including encryption, which scrambles messages so they cannot be read without knowing a specific decryption key; authentication, which verifies user-access identities through passwords; and access control, which limits certain users to see only certain data. Other techniques include firewalls that create virtual walls between trusted networks and the internet, and virus scanning software that detects malicious programs.
How is Data analysis used in computing?
Data analysis involves collecting information from multiple sources and seeking to understand it to discover patterns, trends or correlations. By analyzing different sets of data side by side, we can spot relationships that might not have been noticed otherwise. Companies often use data analysis to gain strategic advantages over competitors by seeking to predict future trends.
How do computers learn from Data?
Computers and computer-driven machines can “learn” using algorithms with large sets of known inputs called training datasets. These datasets contain examples labeled with expected outputs based on certain inputs. The machines apply their learned concepts in new ways, eliminating the need for pre-programming in certain instances.
How can humans benefit from Big Data?
So-called Big Data is regularly used for predictive analytics (predictions about future events) or sentiment analysis (monitoring public opinion about products/services). Businesses use Big Data analytics tools to better understand customer behavior and improve operational effectiveness. Individuals can leverage their own personal datasets for making smarter decisions about their financial investments and medical treatments.
Can Data be visualized?
Data visualization is the process of transforming data into a graphical format, such as a diagram or chart, to help us better understand and interpret it. Data visualization tools come in many shapes and sizes, from ones capable of generating simple pie charts and bar graphs through to others capable of creating complex 3D models and interactive maps.
What are the benefits of Data warehousing?
Data warehousing involves storing data from multiple sources in a central repository so it can be managed effectively with a single source from which to access, analyze and report. Benefits of data warehousing include improved decision-making, enhanced customer segmentation, cost savings from more efficient processes, and reduced manual labor associated with collecting and managing data.
What are the challenges of Data warehousing?
Data warehousing is a powerful tool that can help businesses better understand their operations, but it brings some challenges. One is data quality; it is essential to make sure that the data stored in a warehouse is accurate and up to date. Scalability is another issue, since as data volume grows, the warehouses must keep up. Security is another major concern—with so much sensitive information in one virtual holding area, protecting it becomes even more important.
How can organizations benefit from Data visualization?
Data visualization is a valuable tool because it helps provide context around the trends and patterns found in the data. Visualizations can make large amounts of data easier to digest and make decisions more informed.
