Benefits of Flexible Mobile Data Access

DataSplice provides a dynamic system to help network administrators define and manage the data available to remote clients through a mobile device.

DataSplice has no built-in settings for data access. Every aspect of how it operates with a data source is defined as part of the solution configured specifically for each client's CMMS needs. This makes DataSplice incredibly flexible in terms of what data it accesses and how it can be edited.

DataSplice can be configured to handle data from any ODBC compliant database. In fact, DataSplice can easily access information from multiple data sources simultaneously, even if they run on different database platforms.

A Tool for Successful Data Management

This makes DataSplice an ideal tool for organizing enterprise data from multiple systems. Why purchase expensive upgrades to standardize on a single database platform? DataSplice provides a consistent method to manage enterprise data, regardless of the source. Oracle, SQL Server, or other databases can all be accessed remotely through a consistent interface with DataSplice.

In addition, DataSplice incorporates the same user interface for people working online or offline. This ensures accuracy of work data, and creates a more streamlined procedure for completing updates and changes.

All of the options and settings described in the following sections are easily managed by the Administration Client.

DataSplice Views

Data access in DataSplice is driven by views. For DataSplice, a view is a configurable window into a database that represents a set of records available to the user. By setting up specific views, DataSplice system administrators can control information access, display privileges and editing capabilities.

A view appears on the screen as a grid or table and looks similar to a spreadsheet. In user interface terms, a view constitutes a screen on the handheld. Views are stored as XML files on the server, making it easy to integrate them into source control or other backup processes.

Views in DataSplice consist of:

• View Definition - The information from the database that defines the view and what records are available to a user.
• Data Manipulation - Settings that define how the user can manipulate the view including editing capabilities, field modification privileges, the allowed values for those fields, and much more.
• Relationships - A set of relationships to define how the view is related to other DataSplice views.
• Events - Information about what the server should do when various events are performed, such as creating or updating a record.
• Permissions - Information rights for specific users or groups. This includes access rights to views, fields and editing capabilities.
• View Criteria - Criteria for defining different subsets of data that are available to the user.
• Offline Operation - Offline attributes that define what information needs to be available to a user in batch mode.

View Definition

Defining a view in DataSplice consists of two pieces of information: the source of the data and an SQL statement. The query can reference any valid SQL understood by the target database.

Data sources are defined as connection profiles that specify the ODBC data source to use, as well the username and password needed to connect to the database. There is no limit to the number of connection profiles that may be defined. This enables DataSplice to access any number of available data sources simultaneously.

It is easy to change the connection settings for all views by modifying the main connection profile. This is very useful for moving information from development to production servers.

Authentication for connection profiles can be defined to use a specific username and login for all DataSplice users, or to pass through the credentials of each connection to the database. This enables several different configurations:

• A single, privileged database user and have DataSplice define all database permissions, access rights, etc.
• Connecting with multiple database user accounts and accessing underlying database permissions.
• A combination of both scenarios

This allows DataSplice to take advantage of existing data permissions, or define new permissions that are not currently modeled in the underlying database to provide the desired behavior.

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Data Manipulation

Once the data for a view has been defined, DataSplice provides fine-grained control over how the user will interact with the view. This includes:

• Basic data permissions, such as inserts, updates, and deletes.
• Detailed permissions for each field in a view. This includes how data is presented to the user (naming, formatting, and field widths), and how the user can manipulate the field.

Individual fields can be marked as read-only or provided with default values when new records are created. In addition, lists of valid values for the field can be defined to suggest or restrict data entry for the user.

Field lists can be defined as static list of values (such as valid status codes) or can be dynamically generated by querying a related view with information from a selected record. For example, an equipment field could be configured to use the current location for the work order, to query a parts view, and then create a list of equipment available at that location.

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Relationships

Enterprise data is easiest to manage when it is organized into a hierarchy. For an intuitive workflow, it is important to develop the user interface around the nature of the business task. This simplifies the process for workers that interact with several DataSplice views to complete one particular task.

DataSplice provides the ability to define relationships between views to model relational information. The Remote Client can then use these relationships to present the user with a navigation options to quickly find information. Within a view, a user can pull up lists of data based on context, and then display the correct information for the task at hand.

For example, when accessing parts information for a work order, the user might navigate from a list of equipment to a list of parts. With view relationships, a parts list view will automatically display parts for the current piece of equipment.

Administrators define relationships as filters on a target view using information from the source view. The filters use placeholder attributes to reference data from the selected record to find related records in the target view.

For instance, a relationship from a work order view could use the location of the selected record to display pieces of equipment at that location. This flexible method of defining relationships allows different types of data dependencies to be created in DataSplice:

• Hard Relationships - Parent-child relationships represent a one-to-many or one-to-one association, typically by relating primary key fields.
• Weak Associations - Many-to-many relationships that query related information not part of a parent-child relationship.

The Remote Client interacts with data using the same interface, regardless of the relationships. The DataSplice administrator is responsible for pre-defining how the user will interact with the available data, and save time in the field.

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Events

DataSplice provides a flexible mechanism for defining what the server should do in response to various events, such as updating or creating a record. Because DataSplice must integrate seamlessly with existing master applications, we never create additional triggers or tables that could have side effects for other software accessing the same data.

Event processing can be set up two different ways. The most common method is to perform actions instead of the associated database event. In addition, the server can perform actions before and after the database operation. The latter case is useful to perform data validation, and then pass the event to the database (through an UPDATE or INSERT statement, etc.).

Each event can have a condition that will prevent it from being performed unless certain requirements are met. Conditions are simply logical statements such as "email is not null and measurement >= max". This can be used to take action for data exceptions, and when combined with query attributes can be used to create powerful event processing.

All modifications to the database can be set to perform events - updates, inserts, and deletes. In response to an event a server can:

• Call a database procedure and bind values from the current record to the procedure parameters. Output parameters can be used to modify particular fields. This is useful to automatically generate values for primary keys for instance.
• Send an email with information from the event. This is particularly useful for notifying supervisors of specific "red flag" conditions.
• Call an external program to perform some operation, such as printing reports.
• Execute external code available through server plug-ins. (DataSplice supports code written both in Java and Microsoft .NET.)

In addition, several actions may be chained together for a particular event, with the results, in the case of output parameters, applied to the next action.

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Permissions

Once a view has been defined through the Administration Client, the network administrator needs to specify which users have access to a view, and what events can be performed by that user.

DataSplice supports both view permissions for groups and individual users. This allows DataSplice to support multiple mobile solutions on the same server by simply configuring different sets of permissions for the respective groups.

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View Criteria

Criteria specify subsets of data within a view for different purposes. In practice that means they consist of a filter to narrow the set of records and optionally sort information to return the results in a particular order.

DataSplice supports the following types of criteria:

Default Criteria

These control the default set of data presented to the user when displaying the view.

Offline Criteria

These specify sets of data that should be available to the user offline, such as the user's current list of work orders. This, in combination with sorting capabilities, enable the administrator to specify lists like "the 100 most recently used pieces of equipment" to be available offline.

Mandatory Criteria

These criteria specify user-transparent filters that will always be appended to a query be the server, regardless of the user specified search. This is useful to restrict the sets of data certain users are permitted to see for a view. For instance, mandatory criteria could enforce that records are restricted to a particular location or class of statuses.

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Offline Operation

DataSplice provides powerful capabilities to specify exactly what information is needed for a user to perform work off-site before they leave to complete a task.

Offline operation requires software to capture all data necessary might be needed before disconnecting due to lack of server access in the field. DataSplice also realizes that handheld devices do not have the capability to store and access gigabytes of data.

This is a balancing act because on one side it would be nice to have all information available for a user, and on the other realizing that handheld devices do not have the capability to store and access gigabytes of data. DataSplice has many options to strike a balance so mobile users have the information they need.

Offline Criteria provide the basic elements for defining offline data. These allow administrators to specify sets of data, such as current work lists or parts information for a particular location. Multiple offline criteria can be specified for views, and the administrator can set the maximum number of records available to prevent the remote client from downloading excessively large sets of data.

In addition, view relationships can be used to provide data offline. This enables DataSplice to make key related information available offline as well. For example, if a user's work list is available offline, relationships can be used to retrieve work order details, labor records, and equipment data associated with each record in the work list.

Synchronizing offline data is also very important. The server uses an intelligent algorithm to send only edited information to the remote client. This means that subsequent downloads are much faster in comparison to the initial content download.

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