Astera Data Stack
Version 8
Version 8
  • Welcome to Astera Data Stack Documentation
  • Release Notes
    • Astera 8.0 - What's New, What's Fixed, and What's Improved
    • Astera 8.0 - Known Issues
    • Astera 8.1 - Release Notes
    • Astera 8.2 Release Notes
    • Astera 8.3 Release Notes
    • Astera 8.4 Release Notes
    • Astera 8.5 Release Notes
  • Getting Started
    • Astera 8 - Important Considerations
    • Astera 8 - System Requirements
    • Configuring the Server
    • Connecting to a Different Astera Server from the Lean Client
    • Connecting to an Astera Server using Lean Client
    • How to Build a Cluster Database and Create a Repository
    • How to Login from Lean Client
    • Setting up a Server Certificate (.pfx) File in a New Environment
    • Installing Client and Server Applications
    • Licensing Model in Astera 8
    • Migrating from Astera 7.x to Astera 8
    • UI Walkthrough - Astera 8.0
    • User Roles and Access Control
  • Dataflows
    • Sources
      • Data Providers and File Formats Supported in Astera
      • Setting Up Sources
      • COBOL File Source
      • Database Table Source
      • Data Model Query Source
      • Delimited File Source
      • Email Source
      • Excel Workbook Source
      • File Systems Item Source
      • Fixed Length File Source
      • PDF Form Source
      • Report Source
      • SQL Query Source
      • XML/JSON File Source
    • Transformations
      • Introducing Transformations
      • Aggregate Transformation
      • Constant Value Transformation
      • Data Cleanse Transformation
      • Denormalize Transformation
      • Distinct Transformation
      • Database Lookup Transformation
      • Expression Transformation
      • File Lookup Transformation
      • Filter Transformation
      • Join Transformation
      • List Lookup Transformation
      • Merge Transformation
      • Normalize Transformation
      • Passthru Transformation
      • Reconcile Transformation
      • Route Transformation
      • Sequence Generator Transformation
      • Sort Transformation
      • Sources as Transformations
      • Subflow Transformation
      • SQL Statement Lookup Transformation
      • Switch Transformation
      • Tree Join Transformation
      • Tree Transform
      • Union Transformation
    • Destinations
      • Setting Up Destinations
      • Database Table Destination
      • Delimited File Destination
      • Excel Workbook Destination
      • Fixed Length File Destination
      • SQL Statement Destination
      • XML/JSON File Destination
    • Data Logging and Profiling
      • Creating Data Profile
      • Creating Field Profile
      • Data Quality Mode
      • Record Level Log
      • Using Data Quality Rules in Astera
    • Database Write Strategies
      • Database Diff Processor
      • Data Driven Write Strategy
      • Dimension Loader - Database Write
      • Source Diff Processor
    • Text Processors
      • Delimited Parser
      • Delimited Serializer
      • Fixed Length Parser
      • Fixed Length Serializer
      • Language Parser
      • XML JSON Parser
      • XML JSON Serializer
    • Data Warehouse
      • Fact Table Loader
      • Dimension Table Loader
  • WORKFLOWS
    • What Are Workflows?
    • Using the Workflow Designer
    • Creating Workflows in Astera
    • Decision Task
    • EDI Acknowledgement Task
    • File System Task
    • File Transfer Task
    • OR Task
    • Run Dataflow Task
    • Run Program Task
    • Run SQL File Task
    • Run SQL Script Task
    • Run Workflow Task
    • Send Mail Task
    • Workflows with a Dynamic Destination Path
    • Customizing Workflows with Parameters
    • GPG-Integrated File Decryption in Astera
  • Subflows
    • Using Subflows in Astera
  • Functions
    • Introducing Function Transformations
    • Custom Functions
    • Logical
      • Coalesce (Any value1, Any value2)
      • IsNotNull (AnyValue)
      • IsRealNumber (AnyValue)
      • IsValidSqlDate (Date)
      • IsDate (AnyValue)
      • If (Boolean)
      • If (DateTime)
      • If (Double)
      • Exists
      • If (Int64)
      • If (String)
      • IsDate (str, strformat)
      • IsInteger (AnyValue)
      • IsNullOrWhitespace (StringValue)
      • IsNullorEmpty (StringValue)
      • IsNull (AnyValue)
      • IsNumeric (AnyValue)
    • Conversion
      • GetDateComponents (DateWithOffset)
      • ParseDate (Formats, Str)
      • GetDateComponents (Date)
      • HexToInteger (Any Value)
      • ToInteger (Any value)
      • ToDecimal (Any value)
      • ToReal (Any value)
      • ToDate (String dateStr)
      • TryParseDate (String, UnknownDate)
      • ToString (Any value)
      • ToString (DateValue)
      • ToString (Any data, String format)
    • Math
      • Abs (Double)
      • Abs (Decimal)
      • Ceiling (Real)
      • Ceiling(Decimal)
      • Floor (Decimal)
      • Floor (Real)
      • Max (Decimal)
      • Max (Date)
      • Min (Decimal)
      • Min (Date)
      • Max (Real)
      • Max (Integer)
      • Min (Real)
      • Pow (BaseExponent)
      • Min (Integer)
      • RandomReal (Int)
      • Round (Real)
      • Round (Real Integer)
      • Round (Decimal Integer)
      • Round (Decimal)
    • Financial
      • DDB
      • FV
      • IPmt
      • IPmt (FV)
      • Pmt
      • Pmt (FV)
      • PPmt
      • PPmt (FV)
      • PV (FV)
      • Rate
      • Rate (FV)
      • SLN
      • SYD
    • String
      • Center (String)
      • Chr (IntAscii)
      • Asc (String)
      • AddCDATAEnvelope
      • Concatenate (String)
      • ContainsAnyChar (String)
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      • Compact (String)
      • Find (Int64)
      • EndsWith (String)
      • FindIntStart (Int32)
      • Extract (String)
      • GetFindCount (Int64)
      • FindLast (Int64)
      • GetDigits (String)
      • GetLineFeed
      • Insert (String)
      • IsAlpha
      • GetToken
      • IndexOf
      • IsBlank
      • IsLower
      • IsUpper
      • IsSubstringOf
      • Length (String)
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      • Left (String)
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      • PadLeft
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      • LSplit (String)
      • PadRight
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      • RSplit (String)
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      • SplitString (3 separators)
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    • Date Time
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      • AddYears (DateTimeOffset)
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      • Age (DateTimeOffset)
      • CharToSeconds (Str)
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      • DateDifferenceHours (DateTimeOffset)
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      • DateDifferenceMonths (DateTimeOffset)
      • DateDifferenceMonths (DateTime)
      • DatePart (DateTimeOffset)
      • DatePart (DateTime)
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      • DateDifferenceYears (DateTime)
      • Month (DateTime)
      • Month (DateTimeOffset)
      • Now
      • Quarter (DateTime)
      • Quarter (DateTimeOffset)
      • Second (DateTime)
      • Second (DateTimeOffset)
      • SecondsToChar (String)
      • TimeToInteger (DateTime)
      • TimeToInteger (DateTimeOffset)
      • ToDate Date (DateTime)
      • ToDate DateTime (DateTime)
      • ToDateString (DateTime)
      • ToDateTimeOffset-Date (DateTimeOffset)
      • ToDate DateTime (DateTimeOffset)
      • ToDateString (DateTimeOffset)
      • Today
      • ToLocal (DateTime)
      • ToJulianDate (DateTime)
      • ToJulianDayNumber (DateTime)
      • ToTicks (Date dateTime)
      • ToTicks (DateTimeWithOffset dateTime)
      • ToUnixEpoc (Date dateTime)
      • ToUtc (Date dateTime)
      • UnixTimeStampToDateTime (Real unixTimeStamp)
      • UtcNow ()
      • Week (Date dateTime)
      • Week (DateTimeWithOffset dateTime)
      • Year (Date dateTime)
      • Year (DateTimeWithOffset dateTime)
      • DateToJulian (Date dateTime, Integer length)
      • DateTimeOffsetUtcNow ()
      • DateTimeOffsetNow ()
      • Day (DateTimeWithOffset dateTime)
      • Day (Date dateTime)
      • DayOfWeekStr (DateTimeWithOffset dateTime)
      • DayOfWeek (DateTimeWithOffset dateTime)
      • DayOfWeek (Date dateTime)
      • DateToJulian (DateTimeWithOffset dateTime, Integer length)
      • DayOfWeekStr (Date dateTime)
      • FromJulianDate (Real julianDate)
      • DayOfYear (Date dateTime)
      • DaysInMonth(Integer year, Integer month)
      • DayOfYear (DateTimeWithOffset dateTime)
      • FromUnixEpoc
      • FromJulianDayNumber (Integer julianDayNumber)
      • FromTicksUtc(Integer ticks)
      • FromTicksLocal(Integer ticks)
      • Hour (Date dateTime)
      • Hour (DateTimeWithOffset dateTime)
      • Minute (Date dateTime)
      • JulianToDate (String julianDate)
      • Minute (DateTimeWithOffset dateTime)
      • DateToIntegerYYYYMMDD (DateTimeWithOffset dateTime)
      • DateToIntegerYYYYMMDD (Date dateTime)
    • Files
      • AppendTextToFile (String filePath, String text)
      • CopyFile (String sourceFilePath, String destFilePath, Boolean overWrite)
      • CreateDateTime (String filePath)
      • DeleteFile (String filePath)
      • DirectoryExists (String filePath)
      • FileExists (String filePath)
      • FileLength (String filePath)
      • FileLineCount (String filePath)
      • GetDirectory (String filePath)
      • GetEDIFileMetaData (String filePath)
      • GetExcelWorksheets (String excelFilePath)
      • GetFileExtension (String filePath)
      • GetFileInfo (String filePath)
      • GetFileName (String filePath)
      • GetFileNameWithoutExtension (String filePath)
      • LastUpdateDateTime (String filePath)
      • MoveFile (String filePath, String newDirectory)
      • ReadFileBytes (String filePath)
      • ReadFileFirstLine (String filePath)
      • ReadFileText (String filePath)
      • ReadFileText (String filePath, String codePage)
      • WriteBytesToFile (String filePath, ByteArray bytes)
      • WriteTextToFile (String filePath, String text)
    • Date Time With Offset
      • ToDateTimeOffsetFromDateTime (dateTime String)
      • ToUtc (DateTimeWithOffset)
      • ToDateTimeOffsetFromDateTime
      • ToDateTimeOffset (String dateTimeOffsetStr)
      • ToDateTimeFromDateTimeOffset
    • GUID
      • NewGuid
    • Encoding
      • ToBytes
      • FromBytes
      • UrlEncode
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    • Regular Expressions
      • ReplaceRegEx
      • ReplaceRegEx (Integer StartAt)
    • TimeSpan
      • Minutes
      • Hours
      • Days
      • Milliseconds
    • Matching
      • Soundex
      • DoubleMetaphone
      • RefinedSoundex
  • Report Model
    • User Guide
      • Report Model Tutorial
    • Report Model Interface
      • Field Properties Panel
      • Region Properties Panel
      • Report Browser
      • Report Options
    • Use Cases
      • Applying Pattern to Line
      • Auto Creating Data Regions and Fields
      • Auto-Parsing
      • Creating Multi-Column Data Regions
      • Floating Patterns and Floating Fields
      • How To Work With PDF Scaling Factor in a Report Model
      • Line Count
      • Pattern Count
      • Pattern is a Regular Expression
    • Exporting Options
      • Exporting a Report Model
      • Exporting Report Model to a Dataflow
    • Miscellaneous
      • Importing Monarch Models
      • Microsoft Word and Rich Text Format Support
      • Working With Problematic PDF Files
  • API Flows
    • API Consumption
      • Consume
        • REST API Browser
        • Making HTTP Requests Through REST API Browser
        • Using REST Client Outside of the Scope of the Project
      • Authorize
        • Authorizing ActiveCampaign API in Astera
        • Authorizing Astera Server APIs
        • Authorizing Avaza APIs in Astera
        • Authorizing Facebook APIs in Astera
        • Authorizing QuickBooks API in Astera
        • Authorizing Square API in Astera
        • Open APIs - Configuration Details
  • Project Management
    • Project Management
      • Astera's Project Explorer
      • Connecting to Source Control
      • Deployment
      • Server Monitoring and Job Management
    • Job Scheduling
      • Scheduling Jobs on the Server
      • Job Monitor
  • Use Cases
    • End-to-End Use Cases
      • Data Integration
        • Using Astera to Create and Orchestrate an ETL Process for Partner Onboarding
      • Data Warehousing
        • Building a Data Warehouse - A Step-By-Step Approach
      • Data Extraction
        • Reusing The Extraction Template for Similar Layout Files
  • Connectors
    • Connecting to Amazon Aurora Database
    • Connecting to Amazon RDS Databases
    • Connecting to Amazon Redshift Database
    • Connecting to Cloud Storage
    • Connecting to Google Cloud SQL in Astera
    • Connecting to MariaDB Database
    • Connecting to Microsoft Azure Databases
    • Connecting to MySQL Database
    • Connecting to Netezza Database
    • Connecting to Oracle Database
    • Connecting to PostgreSQL in Astera
    • Connecting to Salesforce Database
    • Connecting to Salesforce - Legacy Database
    • Connecting to SAP HANA Database
    • Connecting to Snowflake Database
    • Connecting to Vertica Database
    • Setting Up IBM DB2 iSeries Connectivity in Astera
  • Miscellaneous
    • Cloud Deployment
      • Deploying Astera on Amazon Web Services
      • Deploying Astera on Microsoft Azure Cloud
      • Deploying Astera on Oracle Cloud
    • Context Information
    • Pushdown Mode
    • Role Based Access Control in Astera
    • Safe Mode
    • Server Command Line Utility
    • SmartMatch Feature
    • Synonym Dictionary File
    • Updating Your License in Astera
    • Using Dynamic Layout/Template Mapping in Astera
    • Using Output Variables in Astera
    • Using the Data Source Browser in Astera
  • Best Practices
    • Astera Best Practices - Dataflows
    • Overview of Cardinality in Data Modeling
    • Cardinality Errors FAQs
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On this page
  • Sample Use Case
  • Using the Reconcile transformation
  • Usage and Benefits
  1. Dataflows
  2. Transformations

Reconcile Transformation

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Last updated 9 months ago

The Reconcile Transformation object in Astera enables users to identify and reconcile new, updated, or deleted information entries within the existing data source.

It can be applied in a wide variety of business scenarios that require a user to identify changes in multiple data records and capture them efficiently to drive critical business decisions.

Sample Use Case

Consider an example where we have sample data of complaints filed by customers regarding the products and services provided by a company. Assume that source file 1 contains details and status of complaints on January 1st, 2018, and source file 2 contains details and status of complaints on February 1st, 2018.

We want to track the progress of the resolved complaints during that one month. To do so, we will reconcile the information contained in the source data files and capture changes using the Reconcile Transformation object.

Using the Reconcile transformation

  1. Drag and drop the Reconcile Transformation object from Toolbox > Transformations > Reconcile on the data flow designer.

This is what a Reconcile Transformation object looks like:

You can see the transformation object contains three child nodes (Output, Input_1, and Input_2) under the parent node, Reconcile.

  1. Expand the input nodes to map fields from the source files.

  1. Map the data fields from the source objects that you want to reconcile to the respective input node in the Reconcile Transformation object.

  1. Right-click on the Reconcile Transformation object’s header and select Properties.

  1. This will open the Reconcile Transformation Properties window where you will see the following options:

    • Case Sensitive – Check this option, if you want to derive a case-sensitive output.

    • Sort Input 1 – Check this option, if the incoming data from source 1 is not sorted.

    • Sort Input 2– Check this option, if the incoming data from source 2 is not sorted

You can choose the Reconcile Output Type from the following options:

  • Side By Side Element With Change Flag – If you want to get values from both sources presented side by side, with a separate column presenting the reconciled output by putting a flag – true, in case of an update, and false if it remains unchanged.

  • Original Layout – If you want to get the reconciled output for each record and corresponding information in the reconciled field.

  • Original Layout With Changed Element Collection – Applies when working with hierarchical data, to reconcile the information contained in child nodes.

Once you have selected the preferred Output Type, you can specify the records to be shown in the output by applying the Record filter and Inner Node Filter. You may choose one, multiple, or all of the following options by check marking the box.

  1. Click Next to proceed to the Layout Builder window. Here you will have to specify a Key. This will be the common identifier in both the source files that will identify and reconcile records. In this case, we want to reconcile the progress on complaints made against each complaint_ID; therefore, we will select Complaint_ID as our Key.

  1. Now go to the Survivor Value drop-down list to set the Survivor Value for each data field. Survivor Values are the values from your source datasets that you want to retain in the output.

You may select from the following Survivor Value options:

  • First – If you want to derive the output value from the first source

  • Second – If you want to derive the output value from the second source

  • First If Not Null, Otherwise Second – If you want to output a value from the first source if the record is not null, otherwise from the second source.

  • Second If not Null, Otherwise First – If you want to output a value from the second source if it is not null, otherwise from the first source.

  • Higher – If the input values are integers, and you want to choose the higher value

  • Lower – If the input values are integers, and you want to select the lower value

  • Expression – If you want to derive the output value based on a formula expression

Note: You will only need to specify the Survivor Value if you want to get the Original Layout or Original Layout With Changed Element Collection as output. The Survivor Value option does not apply if you want to get Side by Side Element with Change Flag as your output, since both of the source values are retained when this option is selected.

  1. Click Next to proceed to the General Options window, then click OK.

  • General Options Window: This window shares options common to most objects in the dataflow.

    • Clear Incoming Record Messages: When this option is checked, any messages coming in from objects preceding the current object will be cleared. This is useful when you need to capture record messages in the log generated by the current object and filter out any record messages generated earlier in the dataflow.

    • Do Not Process Records with Errors: When this option is checked, records with errors will not be output by the object. When this option is off, records with errors will be output by the object, and a record message will be attached to the record. This record message can then be fed into downstream objects in the dataflow, for example, a destination file that will capture record messages or a log that will capture messages and collect statistics as well.

    • The Comments input allows you to enter comments associated with this object.

  1. Now, right-click on the Reconcile Transformation object’s header and select Preview Output to get the reconciled output.

You will get one of the following outputs according to the output type selected in the Reconcile Transformation Properties window:

  • Side by Side Element with Change Flag

  • Original Layout

  • Original Layout With Changed Element Collection

Usage and Benefits

Reconcile Transformation objects can be applied in a variety of business cases, particularly those where monitoring the changes in assorted data records is crucial in driving critical business decisions. Here are some of the benefits and uses of the Reconcile transformation object:

  • Reconciles data by deriving old and new values for specific fields in the source data

  • Allows users to choose from various layout options to reconcile changes in the most appropriate way

  • Works effectively with structured and unstructured (hierarchical) data formats

  • Offers the flexibility to select the information to be retained through different survivor value options

Drag and drop the appropriate source objects and point them towards the files that you want to reconcile. In this example, we will be working with an .

Excel Workbook Source