IST DataProfiler - Data Profiling, Data Assessment, Data Discovery
Data Profiling is the process of auditing data in an existing database
or file and collecting
statistics and information regarding its quality. Often this
additional metadata is referred to as data metrics. Data metrics in turn,
shows
the accuracy and completeness of data which can then be used
for:
- Business
Intelligence - to find out what information is available
in existing data
- Data Quality – to measure and track the
quality of existing data
- Master Data Management – to create
an enterprise view of data across multiple systems
- Data
Integration – to prepare for data integration tasks
- Data Warehouse
and ETL related initiatives
- CRM or ERP implementations
- Understanding challenges
in data-intensive projects
Data Profiling enables business users to leverage traditional IT assets.
In addition, business users often have a better knowledge
of domain and a better grasp of data description, source and
usage.
Data profiling can be performed:
- Before and after data cleansing
- As an ongoing data
monitoring technique
- For every data source as well as
on integrated data
Data Profiling - The First Step in Data Quality Methodology
Recognizing data problems is an important step when designing
data quality procedures. The DataProfiler can provide you
with a better understanding of how to apply data quality
and ETL tools. Processes that would
benefit from profiling include parsing and standardization,
deduping, merge/purge, data integration,
data validation and enrichment, identity searching and matching,
and regulatory compliance.
The DataProfiler expedites the process of learning about your
data. It is an easy-to-use,
configurable solution that provides standardized data metrics
without manual checks.
Ease of Use
The DataProfiler installs and integrates quickly and seamlessly.
Users can install the product, point to a given data source,
drag and drop the desired data metrics, run the profiling
job and review the results.
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