Integrating data quality with your SSIS data flow

Data Ladder’s seamless integration with Microsoft SQL Server Integrations Services (SSIS) empowers users to collect data from any source, clean, compare, and enrich it during migration and integration operations, to gain immediate insight for actionable intelligence.

Integrating Data Ladder’s best-in-class data cleansing and matching solution with Microsoft’s integration and ETL (extract-transform-load) platform allows users to build seamless integration flows with built-in data quality.

With DataMatch Enterprise, you can intuitively test and build scalable data profiling, data cleansing, and data matching configurations and save them in a project. That project can be called within an SSIS data flow to fuse the industry’s fastest and most accurate data-matching solution with Microsoft’s stellar ETL capabilities to help you integrate clean data across the enterprise.

Gain immediate insight with actionable intelligence using data you can trust.

See how independent studies rate Data Ladder’s data quality solutions when compared against industry leaders:

Features of the Solution	Data Ladder	IBM Quality Stage	SAS Dataflux	In-House Solutions
Match Accuracy (Between 40K to 8M record samples)	96%	91%	84%	65-85%
Software Speed	Vary Fast	Fast	Fast	Slow
Purchase/ Licensing Costs	80-95% below the competition	$370K+	$220K+	$250K+
Time to First Result	15 Minutes	2 Months+	2 Months+	3 Months+
Comments	Above tests were completed on 15 different product comparisons with university, government, and private companies (80K to 8 million records). This includes the effect of false positives.	Need multi-threaded, in memory, no-sql processing to optimize for speed and accuracy. Speed is important, the more match iterations you can run, the more accurate your results will be.	Include base license costs, 2014 process or later, in-house, includes salary + benefits. Not in-house implementations had a 10% chance of losing in-house implementations had lost the core member who ran and understood the matching program.	A metric for ease of use. This is the time of rist result, not necessarily full cleansing.

Integrating DataMatch Enterprise with Microsoft SSIS

Let’s say you have an SSIS data flow that receives customer information from a variety of sources and then integrates this data into your Microsoft Azure database, which contains your customer master data.

Trouble is, without cleaning and comparing all those different sets of customer data you’re processing, you will inadvertently end up polluting your master data.

By plugging a DataMatch Enterprise project into your dataflow, you can quickly and easily conduct a cogent profile analysis of data quality, apply a variety of pre-built data cleansing transformations, leverage 300,000+ standardization rules for name, address, and phone matching, and finally compare records to deduplicate, enrich, and create golden records.

Once that’s done, your data continues its journey to your final destination: your customer master database.

Data Cleansing Operations Available

See More Data Cleansing Operations Here

Data Matching Capabilities Available