Time Series Database Management
For Microsoft Windows.
Excel has many features that statistical staff need, such as operating ease, worksheet publishing, analytical tools, graphics features, linking and consolidating features, charting capabilities, and web publishing and browsing functions. It is widely accepted as the main software to handle daily statistical work in most corporations. However, even though the most recent version of Excel has made many improvements in its data mapping and database capabilities, it is still not powerful enough to manage time-series data in particular. The wide acceptability of Excel and its popularity as an end user tool provide third-party developers the incentive to develop an approach that uses a specific database system to interpret information for Excel and, thus, significantly strengthen the power of spreadsheets in handling time-series data.
Dbank for Windows is specifically designed to meet all the standard requirements for efficiently and effectively filing time-series data. Dbank provides a ready-to-use relational database management system (RDBMS) for managing time-series data. Doing so provides for efficient and rapid access to specific time series, as well as accommodating the need to store core attributes or “metadata” for each time series. The standard version of Dbank uses the Microsoft Access database engine to hold the time-series information. However, Dbank allows you to easily replace the Access Engine with a more robust filing system, such as SQL server, Oracle, or Sybase.
Dbank for Windows has a completely open architecture with a built-in graphical user interface (GUI). The main data object of the system is the time series. Users can easily create, name, and read data values; store them in a database for later retrieval; and update, display, and use data in reports, graphs, forecasts, and analyses.
Dbank for Windows also has the ability to create new series from existing series, using an extensive “Series Make” facility. It also provides numerous tools for managing, manipulating, viewing, and plotting time series. It can handle various data frequencies including multi-year, annual, semester, quarterly, monthly, weekly, or daily periodicity. The daily frequency allows for specifying a 5-, 6-, or 7-day week. It has a “NULL” frequency, which allows the user to handle cross-sectional or undated data. It also has basic built-in statistical tools, which allow users to perform statistical analyses and economic forecasting. These tools include summary and descriptive statistics, such as correlations, covariances, auto-and partial-correlations, and linear regressions.
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