This scenario applies only to a subscription-based Talend Platform solution with MDM or Talend Data Fabric.

This scenario describes a five-component Job that generates data records in the form
of tasks and loads them into the stewardship console database.

These tasks will need later the intervention of an authorized data steward to merge,
compare and resolve the data records that are held in these tasks. For further
information, see
Talend Data Stewardship Console
User Guide.

In this scenario:

• A tFixedFlowInput component generates input
  data flow that has five columns: Source, Firstname,
  Lastname, DOB (date of birth), and
  PostalCode. This data has problems such as duplication,
  first or last names spelled differently or wrongly, different information for
  the same customer, etc.

• A tMatchGroup data quality component carries
  out matching operations on data across the heterogeneous sources defined in the
  input Source column. This component groups the output
  columns by a blocking value to optimize the matching operation and compare only
  the records that have the same blocking value, the Source
  column in this scenario. For more information on grouping output columns and
  using blocking values, see tMatchGroup.

• A tMap component filters the input flow into
  unique data records and data records that have matching distances.

• The unique data records are displayed on the Run console via the tLogRow
  component. All other data records that have a matching distance are sent to the
  
  Talend Data Stewardship Console
  database through the
  tStewardshipTaskOutput component and are
  displayed in the stewardship console. An authorized data steward can then
  intervene to merge the data records with matching distances.

For detail information about related scenarios, see Scenario 1: Generating functional keys in the output flow and
Scenario 2: Comparing columns and grouping in the output flow duplicate records that have the same functional key.

• Drop the following components from the Palette onto the design workspace: tFixedFlowInput, tMatchGroup,
  tMap, tStewardshipTaskOutput and tLogRow.

• Connect the first three components together using the Main link.

• Double-click tFixedFlowInput to display the
  Basic settings view and define the
  component properties as described in Scenario 1: Generating functional keys in the output flow.

  The tFixedFlowInput component generates an
  input data flow that has five columns: Source, Firstname,
  Lastname, DOB (date of birth), and
  PostalCode. This data has problems such as duplication,
  first or last names spelled differently or wrongly, different information for
  the same customer, etc.

• Double-click the tMatchGroup component to
  display the Basic Settings view and define the
  component properties.

• Click Sync columns to retrieve the schema
  from the preceding component.

• If required, click the Edit schema button to
  view the input and output schema and do any modifications in the output
  schema.

• In the Key definition table, click the
  [+] button to add to the list the columns
  on which you want to do the matching operation, FirstName
  and LastName in this scenario.

• Click in the first and second cells of the Matching
  type column and select from the list the method(s) to be used for
  the matching operation, Jaro-Winkler in this
  example.

• Click in the first and second cells of the Confidence
  Weight column and set the numerical weights for each of the
  columns used as key attributes.

• Click the [+] button below the Blocking Definition table to add a line in the table
  then click in the line and select from the list the column you want to use as a
  blocking value, Source in this example.

  Using a blocking value reduces the number of pairs of records that needs to
  be examined. The input data is partitioned into exhaustive blocks based on the
  data source. This will decrease the number of pairs to compare, as comparison is
  restricted to record pairs within each block.

• Double-click the tMap component to open the
  Map Editor.

The input area to the left is already filled with the input schema coming from the
previous component in the Job design.

• Click the [+] button in the upper right
  corner of the output area to add as many output tables as needed, two in this
  example uniques and groups. The first
  table will group the unique data records and the second will group all the
  records that have matching distances to the master record in each group.

• Drop the input columns to fill in the first output schema. For further
  information regarding data mapping, see
  Talend Studio User
  Guide.

  All the columns will be automatically filled in the Schema Editor in the below half of the Map
  Editor.

• Click

  

  in the upper right corner of the first output table to add
  a condition to filter the data in the first output table:
  row2.GRP_SIZE == 1.

• Drop the input columns to fill in the second output schema and add the
  following filter: row2.GRP_SIZE > 1 ||
  !row2.MASTER.

• In the Schema Editor of the second output
  table, click the [+] button to add two extra
  columns: weight and istarget. The
  first to measure the matching distance and the second to decide if the record
  will be a target record or a source record.

• Click Ok to close the Map Editor.

• In the design workspace, right-click tMap and
  select the uniques link and drop it on the tLogRow component. Do the same to connect tMap to tStewardshipTaskOutput with the groups
  link.

• Double-click the tStewardshipTaskOutput
  component to display its Basic settings view
  and define the component properties.

• In the Schema list, select Built-In and click the […] button next to Edit
  schema to open a dialog box.

The data is collected from the columns defined in the groups
output table in the tMap component.

• Click OK to close the dialog box and proceed
  to the next step.

• In the Url field, enter the URL for
  connecting to the stewardship console database.

• In the Username and Password fields, enter your login and password to connect to the
  MDM server.

• In the Task name field, enter a functional
  name for the task you want to list in
  Talend Data Stewardship Console
  .

• From the Type list, select the type of the
  tasks you want to write in the stewardship console: Resolution or Data. In this
  example, only resolution tasks are to be written.

  For further information on task type, see
  Talend Data Stewardship Console
  User Guide.

• In the Created by field, enter between
  inverted commas the name of the task creator, Administrator
  in this example. The task creator corresponds to the users of
  Talend MDM Web UI
  . For further information, see
  
  Talend MDM Web UI
  User Guide.

• In the Owner field, enter between inverted
  commas the name of the task owner, the user to whom the task is assigned,
  Administrator in this example.

• In the Star field, enter between inverted
  commas the number of stars, 0 through 5, you want to assign to the task in the
  stewardship console to highlight importance.

• In the Tags field, enter between inverted
  commas the name of the tag category associated with the tasks you want to read,
  not used in this example.

  For further information, see
  Talend Data Stewardship Console
  User Guide.

• From the Looping column list, select a column
  in the input schema on which to base the loop, GID in this
  Example.

• From the Source/Target selector list, select
  the column that will decide if the record will be a target record or a source
  record.

• From the Source list, select a source column
  in the input schema.

• From the Score list, select the matching
  score column in the input schema.

• From the Weights list, select the column that
  defines the matching distance for the input columns.

• In the Extra info table, click the

  

  button to add one or several rows that you can use to add
  extra information to one or several record in the created task.

• In the Title column, enter between inverted
  commas the role of the person who adds the information.

• In the Info column, enter between inverted
  commas the extra information you want to attach to the selected column.

• Click in the Scope column row and select from
  the list the record to which you want to add the extra information,
  PostalCode in this example.

  This will append a red mark to the PostalCode column
  when we open the relevant task in
  Talend Data Stewardship Console
  

When the data steward place the pointer on this mark, the attached information will
display. Such information may help the steward in resolving the data record.

• In the Record Column table, click the

  

  button to add the rows you want to show in each of the
  tasks to create in
  Talend Data Stewardship Console
  .

• Click in each of the rows and select the column you want show in each of the
  created tasks. In this example, each task must have four columns:
  Firstname, Lastname,
  PostalCode and DOB.

• Double-click the tLogRow component to display
  its Basic settings view and define the
  component properties.

• Save your Job and press F6 to execute
  it.

The Run console displays the four columns from the
input flow.

The identifier for each group (task) is listed in the GID column
next to the corresponding record. The number of records in each of the tasks is listed
in the GRP_SIZE column and computed only on the master record. The
MASTER column indicates with “true” that the corresponding
record is a master record. The SCORE column lists the calculated
distance between the input record and the master record according to the Jargo-Winkler matching algorithm.

All other input records that have a matching distance are listed in
Talend Data Stewardship Console
waiting for a data steward to merge, compare and
resolve the data records.