Analytics is the core of running the business with deep insight for decision making. Running the business is better or rather say best, when the platform is SAP HANA. The critical fuel for analytics is right data. Data can be raw and as is or it can be enriched and improved to make it meaningful. Data Integration with Data Quality is the key to procure and make data meaningful. In this session we will be sharing level two information about SAP HANA Smart Data Integration and Smart Data Quality with additional information on Data Virtualization.
The legal disclaimer applies
Everything subject to change
SAP assumes no responsibility.
Use interface
Take advantage of SAP HANA memory speed
Capabilities in SAP HANA
Operational/analytical use cases
SDI – real time, batch, ELT
SDQ – data quality – data cleansing, geo-coding matching
Embedded in SAP HANA
Can deploy on premise or in cloud
Supports IT team
Development tool for IT team
Access, move, transform, cleanse data in real time or batch
One HANA platform
Part of HANA platform
From any data source
SDI – ingest data from wide variety of data sources
Combines capabilities of SAP Data Services and SLT
Get changes in real time depending on type of source
Can be log based scanning
Some cases is trigger based, resembling SLT
Can send data back into certain targets; check PAM
Use SAP WebIDE going forward, use URL to access design time
Install agent on premise
Agent acts as a proxy
On premise use TCP/IP; use HTTPS in cloud
Agent compresses data (to minimize bandwidth) and sends over TCP/IP in HANA
DP agent can be downloaded from SMP
Connect to DP Server
Transformations executed in calc engine
Supports design time artifacts
Drag and drop interface
Flowgraph
Available transformations
Supports real time
RestAPI can be used in consuming applications
Not all transformations are available in real time
Replication task is another artifact
Single or mass replication
Basic transformations
Data masking to protect information with SSL
Data masking transformation
Different data masking variants
In-built capability for data quality; part of SAP HANA
Use in-memory capabilities
Cleanse transformation to identify duplicates
Match transformation
Geocode transformation to enrich data with lat/longitude
Reverse geo coding to provide address
Geocoding integrates with HANA spatial
Executes on the script server
Turn on script server and data provisioning server
SDQ helps get accurate geo code information
Real time data quality check and verification
Data Hub manages data movement
Outlook for Data Hub; SDI/SDQ already there
ADP is a work in progress
Data Hub architecture
Road map was not covered during webcast
Road map was not covered during the webcast
Source: SAP
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