Which Of The Following Best Defines Big Data?
“Which of the following is not a data type?” is the most common question asked by most of the analysts, programmers and other people involved in big data and artificial intelligence research. Although the exact answer to this question may never be known, thanks to advanced technology we are slowly discovering answers to this question on a daily basis.
Data is obviously the key to success for any business. Big data and advanced technologies allow businesses to gain access to extremely large amounts of information that previously had been deemed too difficult or even impossible to process. With this information businesses can make informed decisions about their customers, products and other assets. This allows businesses to create profitable solutions to complex problems by providing an accurate solution to a specific problem. Data can also allow businesses to find emerging trends and opportunities which have the potential to become major successes over time.
However, what exactly constitutes “data” and “is it good enough” comes into play when answering this question. Data can either be qualitative or quantitative and the data itself can be a mixture of both. For example a sales order entry can be considered as data which contains both qualitative and quantitative information such as date, time, invoice number, name and address of the customer, purchase amount, customer’s authorization code and many other parameters.
Therefore, which of the following best defines a data type? The simplest answer to this question is a database approach. A database approach is defined by a collection of systems and tools that enable users to access and manage their data. One example of a database approach is Microsoft Access where users gain access to their data through a variety of software systems. Another example is the relational database management system that stores data in tables and allows users to access the data stored in the table from any source. In addition to using a database an IT team may use a new system which is called a data warehouse which stores unstructured data in an organized form that the IT team can use to perform a wide range of analytics and business tasks.
The second answer to the question “which of the following is not a data type?” is a (q) data type which combines the capabilities of a database and of an Access database. An example of (a) would be a (R) row index, which enables users to easily retrieve rows for which a name has been entered. An example of (a) would be the XML schema, which allows developers to easily define data structures for a (R) data type.
The third answer to the question “which of the following is not a data type?” is a (q) data type, which maps directly to a primary key. An example of (a) would be the (T) time table which maps directly to the time fields in the database. Another example would be the (q) bin table which maps directly to the database in tables. An example of (a) could also be the (T) text index which maps directly to the text fields in the database. One more example of a (q) is the (S) simple index which maps directly to the Text attribute in the database.
The fourth answer to the question “which of the following is not a data type?” is a (t) data type which is used with complex queries. The example of (t) would be the (f) Meta tag(s), which maps directly to Meta tags and (v) sub-aggregations which maps to database columns. Another example would be the (p) partial path that maps to a single column in the database. The (o) is the (t) empty record which is not a part of any database approach and (v) normalizer which maps directly to normal form.
The last answer in the list is (a) which of the following best describes a user accesses data through a web application. An example of this data type would be a web form that a user fills out using data provided by an outside source such as a web server or a browser. The database used for storing the answers to (a) above would be the (R) resource record which stores all resources accessed by the user throughout the program. For an explanation of (a), see the Data Dictionary.