What is Signals
Signals is an instrument to observe the variation of the data differentiating it from the statistical noise. Morphs are mutable objects, which can be sent to interested recipients, which encapsulate the data, the related context, the variation charts, automatic and user annotations that act as translators for the different actors interested in knowing the meaning of the march. of its critical processes.
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Fig. 27. Signals full screen
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Control Panel
Through this screen area you select what specific KPI & project you want to see. The panel consists of the selection lists and a project indicator, and a series of controls that act on this selection:
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It may be that for certain projects or indicators has no data yet. Both the list of project indicators like you to determine where to look, with different emphasis in italics detect items with less data (or no data). This allows you to quickly select those parameters that return meaningful data
Charts and data panel
It is the area where you can see the process control charts and data table for the selected indicator through the Control Panel. In the top panel, the graphs X and mR (Normal Distribution and Variation) will show the distribution and variation of the data in graphical form for a better appreciation of patterns, while the bottom, the numerical data table, complete its view with the corresponding numerical values. Explore this table using a contextual menu (right click) menu or View menu bar to search for text data, display the minimum, maximum, or average. Meanwhile the graph X can be filtered with the "View" menu by selecting points on the graph with the mouse to mark:
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You can share the charts and exporting data table to external files or send them by email.
Fig. 28. Example of a Panel Data type indicator Bar
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Charts
Charts are one of the three components of the statistical analysis system (along with data values and context) that allow variations to be visualized to help control processes by establishing their causes. There are three types of charts (lines, bars, and circles). The former are used in process control. The labels correspond to signs of variation (various types, identified with a color). It is convenient to filter the period using sliding the horizontal bar to dynamically visualize the changes. The magnitude of the variations is plotted on the curve below, called the mR graph.
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Con role Developer: Puede inspeccionar cada morph y el modelo con las opciones correspondientes del halo
Data
The data should always be considered in conjunction with the other components of the analysis: graph and context. Numerical data (which can be aggregated) always correspond to a project (or set of projects of the same type), and a period. The data panel is displayed decorated with the colors and names of the statistical signals
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#instrumentos: type of issue
#operations: states of the process flow
#actors: user / user group names
Fig. 29. Example data showing patterns
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Metadata
The metadata of an indicator (category "Activity System") consists of information added to its value related to the Activity System involved, and is represented by values related to its components, specifically the instruments, operations, and actors involved in the activity measured by the indicator.
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To indicate that your indicator supports metadata, remember to categorize it as "Activity System" (see examples) and qualify the RQL code with metaCode: (if you do not provide a specific code, the application will try to derive it from code: common)
Context
The context that must accompany any set of data and graphics. The context provides situational information that allows explaining and understanding the other components as a whole. It has several levels: KPI context (objective, formula), data (quality index, entropy), project (typifications), user (comments, global annotations) and complementary graphics.
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With Developer role: you can use Morph halo to manipulate context components
Fig. 30. Context Inspector
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Fig. 31. Data panel context
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Library: User defined measures
It is recommended that each organization defines its own plan of measurements, can even begin to work with factory available indicators. The implementation of this plan will be made by any of the following methods available, depending on the nature of the specific indicators required:
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Coding of new indicators from the measurement data base (or adding the necessary attributes of existing sources or new tools). The user has a high-level language and analytical capabilities created by IMPROVEKIT called IHDSL. This language is similar to SQL, but also to allow use in conjunction with the Smalltalk object-oriented language, contains specific operators for data analysis, for example, search for particular signals. The runtime support and debugging, syntax highlighting, complete fields are a real development environment. The data sources are specified in SQL (if desired, the user or IMPROVEKIT on demand, may also encode indicators in SQL)
Open Measures...Fig. 32. Editor user-defined indicators
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Smart categories
They consist of a form of indicator and project filters, defined by the specific IHDSL domain language. In this way, you can define dynamic categorizations according to whether a condition (true, false) is met. The categories can be accessed from the browser or from the menu of scripts (bundles).
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prj performance = 'muy alto'
Inspector
You can find more information on the selected indicator by this panel, so to have in one place the (numerical and graphical) analytical information you need: average values, boundaries, graphics and histogram intervals, pareto (for certain types of indicators)
Detailed View
You can explode each point, bar or portion of any indicator to check the source of its information. To do this, double click on the item to explore and will open in a new window query for the data source involved.
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Note: in order for you to have a comprehensive information context, information is displayed (with the aforementioned possibility of filtering) of the data source for the period involved
Fig. 33. Example of an indicator's data source
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Working with indicators
View indicators
With the Repository Browser tool you can perform operations with the set of indicators present in the organizational repository of measurements, such as search, filter, query, analyze values, update, etc..
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Underlined: those indicators whose number of records exceeds the set threshold (see View menu option)
Bold: user-defined indicators (with the application or externally as JIRA filter or Redmine)
Italic: indicators as number of records is not significant (<= 7) for statistical analysis
Strikeout: inactive indicators
Maintain indicators
You can define external indicators (in Redmine for example) to be viewed in conjunction with other indicators in the tool Repository Browser.
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To add new indicators have several options (see "User-defined Measurements"), one of which is self-generate through the menu option
Search Indicators
You can look for indicators in organizational measurement repository in several ways, according to each need:
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Fig. 34. Search metrics in a tool by text
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View Indicators
You can consult an indicator using the data repository tool by selecting the indicator and a project. By default is selected project data, grouped by "phase". You can also consolidate information for the selected project category (for example size). You should always select the project, since it is used for both searches per project to consolidate information by type of project. Depending on the indicator, you can configure the query search more parameters: weekly detail instead of phases of the project, detailed grouping by project category ("baselines") and trends (per phase and project category).
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Fig. 36. Chart circular type (three series)
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View same indicator for other project's group
You can quickly see the same indicator at selected but for another project category using the menu option "Go". This will not need to select any project for organizational or baseline clustering corresponding to a category of projects (for example, by size) and is useful for comparing the same indicator in different projects category
Compose a
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Story
To monitor processes is useful to focus visually information easily accessible. To do this, you use the Dashboard tool, which allows you to perform data analysis of a set of indicators, and other activities as record "baseline" (or comparison), share data with other users and the observations made. Control panels must be constructed selecting indicators of measurement repository. To assist in this task, you have the following options:
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Fig. 37. Building a Dashboard based on change patterns
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Working with charts and numbers
Share information
You can share the graphics and table with numeric values by exporting to image files and external text using the menu option "Share" or send them by email (by default, to the project leader)
Filter indicators data
To analyze subsets or exclude certain values, for example due to particular circumstances, for error in data capture, or peaks that should ignore in the analysis, you can filter the points curve graphs excluding particular points to note the beginning or end of the series via the context menu (right) pointing to a point on the graph.
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You can keep the filters from-to-exclude from the morphs of the desktop synchronized
Fig. 38. Manipulating the data serie example
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Identify values
Relate the points on the graph and number table will help you understand the whole information in both formats. Point to any point on the graph with the mouse to display information related to it, or request identification number table, which is valid for position values, refer to as the minimum, maximum and average. In long series can find projects, periods or particular values in order to direct access to the measurement
Annote a (curve) chart
You can annotate graphics with text to indicate comments, that will be persistent when saved the work environment. You can return to viewing (or hide) through contextual menu (right) graph panel. Other automatic annotations allow you to:
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Fig. 39. Annotation example
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Add series to a chart
To visualize relationships and possible correlations between indicators, you can compose a graph of curves with series of one or more indicators (indicator is usually the same, but you can use any indicators curve). To add an extra series to an indicator, you must first have open the base graphic in a new window (or a page of the scorecard) and by using the chart context menu (right click on it) select "add extra series". You can add as many additional sets as you want (each range is displayed in a different color).
Add a polymetric serie
You can display in graphical form relationships between two indicators, for example, add information from a duration indicator to a efforts scorecard to see the relationship between two variables. This way you compose with a curve type indicator, one polymetric, which takes information from two indicators. You can see the extent of the second variable depending on the size of the related point, according to their value
Fig. 40. Relating two indicators in one chart example
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Analyzing data distribution (Pareto)
You can display concentrations in graphic data to determine the most important factors of a, typically large set of factors. To do this, use a chart type "Pareto" graph contains bars and lines where individual values are represented in descending order by bars, and the cumulative total is represented by the line. In quality control, the Pareto chart often represents the most common cause of defects, type of defects with higher occurrence, or the most common cause of customer complaints
Fig. 41. Viewing values grouping and concentration example
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Analyzing data buckets
When variables will take a large number of values or the variable is continuous, you can graphically display data clusters in class intervals, allowing you to see the count and repetition frequencies of data easily
Compare using diffuse signals
Diffuse signals are qualitative variations in the data of one indicator relative to another set of data that are calculated using fuzzy logic. Each signal corresponds to a variation pattern of a set of fuzzy values (high, low, medium and intermediate) that can be displayed with the option View Tags | Diffuse Signals.
By default, the set of data to which they are compared are organizational aggregates for the same project type as the selected one. Alternatively, you can select another data panel (with the same indicator as the one selected) from the desktop or the dashboard as comparable, so that your data will be taken as the basis of comparison (for example you could qualitatively compare the values between two projects, set of projects , Or the same project in different periods)
Configure charts colors
For best viewing (and considering special visual capabilities), you can define a range of colors for charts of indicators, from the selection of a basic color range. On the other hand, preferences menu allow you to set default data signals color
Data
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Panels
Data panel
Like graphics, data grids can also be displayed as morphs on the desktop. The data can be the values of a data panel that accompanies the graph of an indicator, or query results (written by the user in IHDSL or as a result of exploring a particular point in detail).
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The bottom / center icon of the morph allows you to open an IHDSL script editor so you can write queries with the data to open other grids / graphs or generate new metrics stored in the measurement repository. If the IHDSL code was saved to an external file, the data grid it generates can be kept up to date by selecting the option Refresh.
Fig. 42. A data panel
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Charts
From the halo menu of a data grid you can graph the value of a selected numeric field. The generated graphic opens as another morph on the desktop, retaining the context (the data itself).
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