Data flexibility is a quality characteristic.
Flexibility in accessing data
Can span longer distance, fewer data paths, flexibility in design, error detection,
The Data Market Monitoring provides one with product flexibility along with other options for customizing the periodic reports in order to suit the requirements of the clients.
You can keep it for headings. It can also give you flexibility to add in more data easier at the top.
oVirtual simulationoReduction of the cost of productoTime wastage reducedoVersatilityoHigher qualityoIncreased design data integrityoIncreased design flexibility
A data lake is a storage repository that holds a vast amount of raw data in its native format until it is needed for analytics applications. While a traditional data warehouse stores data in hierarchical dimensions and tables, a data lake uses a flat architecture to store data, primarily in files or object storage. That gives users more flexibility on data management, storage and usage.
Reports allow you greater flexibility in grouping and summarising data compared to printed forms.
Data Redundancy and Inconsistency: Data redundancy: The presence of duplicate data in multiple data files so that the same data are stored in more than one place or location. Data inconsistency: The same attribute may have different values. Program-Data dependency The coupling of data stored in files and the specific programs required to update and maintain those files such that changes in programs require changes to the data. Lack of flexibility A traditional file system can deliver routine scheduled reports after extensive programming efforts, but it cannot deliver ad-hoc reports or respond to unanticipated information requirements in a timely fashion.
Storing data as text in a database allows for easy manipulation and querying using text-based functions and tools. It also provides flexibility in terms of accommodating different data formats and structures. Additionally, text data is human-readable, making it accessible for analysis and reporting purposes.
It can be called hard coding the data. For many things in computing it should be avoided if possible in favour of using variables or defined constants, in order to give more flexibility and structure to a program.
Advantages: Access to data even without internet flexibility Total control over the system High personalization possibilities Disadvantages: personal responsibility for data staff costs Costs for maintenance, support and updates