What is a Data Service Application?
What is an Information Supply Chain?
How is the DataLens System different from an ETL (Extract, Transform, Load) System?
Doesn't my PIM or MDM system negate the need for the DataLens System?
Why can't I just use my existing applications to clean and enrich my product data?
How difficult is it to learn and use your system?
What database do you use?
Why is it called the DataLens System?
What is a Data Service Application?
Data Service Applications are composite applications that can be called as a data services to solve complex data processing tasks and are available for reuse with any enterprise system or Information Supply Chain.
Data Service Applications are built in a code-free drag-and-drop environment that is fast to build and inexpensive to maintain. Also, because these Data Service Applications use Data Lenses to interpret and standardize data, they are "aware" of data quality issues and can incorporate sophisticated exception management to not only integrate data between systems, but assure its quality and reliability in the process.
What is an Information Supply Chain?
Information Supply Chains are the data equivalent of the physical supply chains that move products from manufacturer to supplier. Information Supply Chains carry product information between systems, users and organizations to enable efficient e-commerce and any number of other business operations, from product design to inventory to businesses intelligence to customer service. Throughout the Information Supply Chain, wherever data is not "right", business suffers.
How is the DataLens System different from an ETL (Extract, Transform, Load) System?
Most ETLs are primarily about extracting and loading data — in other words, moving it between systems. The "transform" portion is really limited to relatively simple mapping of structured fields in a rote fashion. Any significant understanding, restructuring, enrichment, translation, data quality or exception management would most likely be handled using other tools. To the extent that an ETL tool does complex transformation, it generally uses external custom code and scripts that are expensive to create and unreliable in operation.
Data Service Applications created by the DataLens System complement ETL systems in that they can be called by the ETL system to handle complex transformation, mapping and exception management as part of the ETL process. In simple ETL scenarios, the DataLens System can also "Extract" and "Load" and perform all the basic functions of ETL.
Doesn't my PIM or MDM system negate the need for the DataLens System?
No, the DataLens System complements PIM (Product Information Management) and MDM (Master Data Management) systems. In fact, Silver Creek Systems has partnered with the most prominent PIM and MDM systems for exactly that reason.
PIM and MDM systems store and synchronize a single, central source of truth across many enterprise systems, but first require "golden" reference data — data that is complete, consistent and correct. The DataLens System can automate the match, merge, transform and validation processes to create "golden" reference data that can then be used in PIM and MDM systems.
Why can't I just use my existing applications to clean and enrich my product data?
Traditional tools can work well for fairly static data, data that doesn't often change such as customer data. Dynamic data, such as product data, is subject to an ever increasing stream of electronic information derived from an ever increasing number of systems and suppliers. Traditional tools and manual processes just can't keep up and are too costly.
How difficult is it to learn and use your system?
Our customers and users consider the DataLens System to be very easy and intuitive to use. The "no code" interface allows business and semantic rules to be maintained by business people with no IT intervention required — a significant win for both business and IT users.
What database do you use?
None, the DataLens System does not store transactional data. As a data service, it processes data (synchronous or asynchronous) and sends back a result. This simplifies enterprise integration and it avoids creating yet another data store to be maintained and managed.
Why is it called the DataLens System?
If you think of an optical lens, it does not store anything and it operates inherently in real time. Data Lenses do the same with data — they let you "see" your data in real time, but in a different form — transformed or refocused — according to how you want to see and use it.
