For the others posts, see
Each chapter in the book starts with a quote (or two) and for the chapter about data integration, we quote a physician/writer, a developer, and a behavioral economist.
I have no data yet. It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts
—Doyle, A.C (1892) The Adventures of Sherlock Holmes, A Scandal in Bohemia
You can read the story on Gutenborg.org or listen to the radio drama (quote at 3:55).
If you have no idea who Sherlock Holmes is, see the Ted-Ed lesson
Garbage in, garbage out
—Stephen Wilfred (Wilf) Hey
After first-in, first-out (FIFO) and last-in, first-out (LIFO). The GIGO principle also applies more generally to all analysis and logic, in that arguments are unsound if their premises are flawed.
Also phrased as “Garbage In, Gospel Out” referencing an overtly optimistic view about what computers can produce [Wikipedia article]. Excluding machine learning, of course.
Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone… http://t.co/tREI1mRQ
— Dan Ariely (@danariely) January 6, 2013
… else is doing it, so everyone claims they are doing it.
—Dan Ariely, professor of psychology and behavioral economics
His books are best sellers and his TED Talks have been watched by millions, e.g. what motivates us to work?
For more information, visit danariely.com.
Ariely expressed irreverently an on itself respectable opinion at the time, as attested by Gartners Hype Cycle for 2013.
If you are not familiar with hype cycles, here is an explanation
For the latest Gartner hype cycle, see
In the original manuscript, a long list of references to other material was included, which for space constraints and other reasons did not made it to the final book.
For example, to avoid any “we recommend ourselves” marketing, other relevant SAP Press titles have not been listed in the book. Otherwise, on the topic of data integration, we would certainly have mentioned:
Below a small sample of some of the topics addressed in chapter 7, SAP HANA Data Integration.
Enterprise Information Management
Data integration is an inclusive topic and in almost every paragraph in the chapter of this book, SAP HANA interacts with products categorized by SAP as Enterprise Information Management.
The technology from SAP Data Services, for example, is also used in SAP HANA Data Integration (SDI) and SAP HANA Data Quality (SDQ) and in SAP Cloud Platform Integration for Data Services (CPI-DS).
In the early days of SAP HANA, when the sidecar scenario was a popular implementation, Data Services provided one of three possible data transfer/replication approaches
- ETL-based using Data Services
- trigger-based using Landscape Transformation Replication Server (SLT)
- log-based using Replication Services
The best answer to the question when to use what, as often, was ‘it depends’ but at times could also be influenced by who you asked, someone from Walldorf or from ex-Business Objects/Sybase employees, still passionate about “their” technology.
Enterprise Information Management is an old discipline in the field of Information Technology. According to Wikipedia, EIM combines enterprise content management (ECM), business process management (BPM), customer experience management (CEM), and business intelligence (BI); SAP offers products in each of these categories.
Old, here, does not mean stale, as developments both at the product level and at the marketing level are in full swing.
SAP HANA Data Management Suite
Last year at SAP SAPPHIRE, the SAP HANA Data Management Suite was announced
The news article includes a video with a cameo appearance of the SAP HANA Academy (near and dear to the heart of this author) at 1:06 “YouTube and online classes are all you need”.
and an infographic with facts and figures (click for full-size).
With more information available about the suite on the SAP Community, in solution briefs, and as strategy talk course available on openSAP.
- SAP HANA Data Management Suite
- Secure, governed, and trusted enterprise class data management (solution brief)
- SAP HANA Data Management Suite – Strategy Talk
SAP HANA Cloud Services
This year at SAPPHIRE, the announcement concerned SAP HANA Cloud Services, defined as a suite of data management and analytics products.
SAP HANA Cloud Services includes SAP Cloud Analytics (generally available), SAP Data Warehouse Cloud (released in beta), and SAP HANA Cloud (under development).
For more information, visit
Wait, There is More
What about SAP Data Hub and SAP (HANA) Vora? SAP HANA Spark Controller? SAP HANA Hadoop Integration?
What about SAP Cloud Platform (Altiscale) Big Data Services that provide Hadoop-as-a-Service or HaaS (not to be confused with HANA-as-a-service or HaaS)?
What about SAP Enterprise Architecture Designer (edition for SAP HANA) and how does this relate to PowerDesigner?
What about SAP HANA Remote Data Sync (RDS) and SQLAnywhere?
How does SDA, SDQ, SDI relate to Agile Data Preparation (ADP) and Enterprise Semantic Services (ESS)?
And how to replicate? With SLT, Data Services, or Replication Server.
These topics, and many others, are the subject of chapter 7, SAP HANA Data Integration.
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