The Lyftron Provider for Mattermark offers the most natural way to access Mattermark data from Lyftron with ease and also enables to connect with BI, MDM & ML tools, Data warehouses, Databases and other SAAS based applications with zero code and zero infrastructure requirements. The provider wraps the complexity of accessing Mattermark data into easy-to-integrate relational fully managed ANSI Sql format. Make faster and better business decisions with Lyftron’s Mattermark data provider and automatically build your data migration pipelines in minutes, not months
The provider hides the complexity of accessing data and provides additional powerful security features, smart caching, batching, socket management, and more.
- Comprehensive Delta load mechanism.
- Real-time access to Mattermark.
- Comprehensive full support of ANSI Sql to query data with ease.
- Collaborative query processing.
The user must have credentials for Mattermark, Lyftron and your destination data warehouse, lake or database to perform the data pipeline operation with Lyftron
Step1: Setup MatterMark account
1.1 Create account in MatterMark and login
1.2. After Login go to -> Setting and click on -> New API Key to generate Api key
Establishing a Connection with Lyftron's Quickstart Steps
Create your Mattermark connection with Lyftron by following the 5 easy steps show below:
Step2 : Login to Lyftron
Start creating your connection
Step2.1 Add your connection
Click on Connect section on the left panel → Click on Add Connection button In the connector selection panel, search and click Mattermark for your connection
Step2.2 Enter your connection details
In the Connection String section enter the values of the below parameters. The following connection string is required to establish Mattermark connection with Lyftron.Profile=Mattermark.apip;ProfileSettings='APIKey=[your_apiKey]';
Give connection name as mattermark -> Replace “your_api_key” with mattermark Api-key , click on test connection -> click save. If connection is not successful so, check the error
|Connection Name||Enter your connection details||Required|
|APIKey||your Mattermark < API Key >||Required|
|Logfile**||Use the logfile option to debug your job and provide your connection name to generate the log file. [ConnectionConfigurationPath]\Connection_name_log.tx||Optional|
|Verbosity**||Choose verbosity 1-5 based on the severity of debugging||Optional|
** For more information, check the Lyftron logging and debugging section.
If you want more detailed information about how to establish a connection with Lyftron, click on Lyftron Connection Quick Start guide.
Test your connection
Once you are done entering your connection details, simply click on the Test Connection button to test the connectivity. In case your connection fails, add Logfile and Verbosity parameters and check the Lyftron logging and debugging section, to debug the error.
Save your connection
Step3 : Normalize
Create data source
After establishing connection, datasource metadata import is needed and for that Lyftron automatically normalize your API & different SQL dialects data into ANSI SQL format and also gives you API sources into simple, code less out of the box data model.
3.1 Click on Normalize section from the left panel -> Click on Add Data Source button, Enter data source name -> Choose MatterMakr from the existing connection list -> Click next
3.2 Choose the table you want to import and -> Click Create
The provider models the data in APIs into a list of tables that can be queried using standard SQL statements.
Generally, querying APIs tables is the same as querying a table in a relational database. Sometimes there are special cases, for example, including a certain column in the WHERE clause might be required to get data for certain columns in the table. This is typically needed for situations where a separate request must be made for each row to get certain columns.
|Companies||Tables||The company list allows you to retrieve all companies, or a list of companies filtered by one or many parameters.|
|Company||Tables||The company list allows you to retrieve details about one company.|
|CompanyEmployees||Tables||This endpoint allows you to retrieve key personnel for a specific company in our database.|
|CompanyNewsArticles||Tables||The company stories endpoint retrieves the 50 latest news articles about the specified company|
|FundingEvents||Tables||Retrieve a list of funding events for a specific query|
|Investor||Tables||Returns details for a specific investor. Information includes the size of their portfolio and some stats around their portfolio and funding deals.|
|InvestorPortfolioCompanies||Tables||Returns a list of portfolio companies for a specific investor.|
|RemainingQuota||Tables||Returns a count of how many API requests you have left in the current period.|
|SearchCompanies||Tables||The search endpoint can be used to query for a company or investor based on a keyword you define, and is also useful to provide autocompletion for common queries, such as by company name or domain.|
|SimilarCompanies||Tables||The similar companies endpoint returns up to 20 of the most similar companies ordered related to the specified company.|
Step 4: Analyze
Querying the data source data
Lyftron allows you to query the source data by simply writing the ANSI Sql query. Please keep in mind as the data is coming directly from API so, there’s a limit to API calls and performance delay from the Stripe API side which Lyftron can’t control so, don’t expect to pull millions of records in just fraction of seconds. If you have heavy data loads, create the pipeline to unload that data into the Lyftron warehouse and query from it.
4.1. Click on the analyze section on the left panel -> Choose data source from the list. Drag and drop the table -> Choose your querying options
4.2. Click on -> EXECUTE and selected query will return data successfully