E/ΔNsc/N0
1.6 Experimental signatures
LESSON OVERVIEW
In this lesson, we will introduce SAP HANA Vora and explain how it fits into an SAP HANA landscape.
LESSON OBJECTIVES
After completing this lesson, you will be able to:
● Describe how SAP HANA Vora enables BI over Big Data
Big Data is Disconnected From Core Business Processes
There is no denying that Big Data is a very hot topic. Many organizations are well down the road on their Big Data journey, collecting and storing staggering amounts of data sourced from sensors, web logs, social media traffic, communication logs and more. Many of these organizations have also implemented specialist tools to process the data from these gigantic data lakes and are now busy mining this data. They can then take the results from big data analysis and combine these results with traditional enterprise analysis using BI tools in order to try to figure out how big data provides additional insight into core operational data.
And there lies the key problem. We know that Big Data and enterprise data needs are typically stored separately, but the analysis should not be separated and business analysts should be able to consume any data.
Building and running queries over Big Data requires the use of specialist tools and query languages. These tools require specialist skills and so are often used by only a few trained people in the organization. They are not mainstream BI tools that are used by most analysts.
Big Data processing tools are often batch oriented and cannot provide deep analytics in real time. Also, Big Data is stored in a very simplistic unstructured way and there is are little or no business models or semantics stored with this data. So we need specialist tools to enable us to treat Big Data like structured data adding in semantics so we can write queries. There have been many tools appearing in the market over the last few years to enable this. But what business analysts want is to simply combine Big Data, enterprise data and in fact any distributed data using familiar BI tools. And of course, this should all be available for real time analytics with exceptional performance.
Bringing Together Core Enterprise Data and Big Data
SAP HANA Vora enables analysts to consume Big Data and enterprise data as one, using familiar drill-down, slice and dice query tools.
Let’s describe SAP HANA Vora from a technical perspective. First, a Big Data framework consists of a data storage component. The most popular is Hadoop. Hadoop provides massive data storage capabilities. But Hadoop does not provide the data processing capabilities and that’s where Apache Spark comes in.
Apache Spark provides the data processing on top of Hadoop, but Apache Spark is not able to provide the OLAP type analysis features over the Big Data data that most business analysts require. And that is where SAP HANA Vora comes in. SAP HANA Vora is an in-memory query engine that runs on Apache Spark and enhances Apache Spark to include hierarchies, including time dependent hierarchies, OLAP style dimensional drill-down/across, unit-of-measure conversion, and currency conversion and many other features. SAP HANA Vora allows us to create pre-compiled queries that are ready to go to enable fast execution.
Figure 92: Bringing Together Core Enterprise Data and Big Data
SAP HANA Vora is designed to work with the SAP HANA platform to provide end-to-end in-memory computing across enterprise data in SAP HANA and Hadoop systems. Both the SAP HANA platform and SAP HANA Vora are also independent products and can be used
separately to support different use cases. The SAP HANA platform does not require SAP HANA Vora to run, or vice versa
You can deploy SAP HANA Vora on an existing Hadoop installation as long as that installation
Unit 4: Data Provisioning in SAP HANA
With SAP HANA Vora you can perform root cause analysis using interactive queries across both business and Hadoop data to better understand business context. You will often hear the expression ‘adding contextual insights to enterprise data’. That is exactly what SAP HANA Vora does, it takes enterprise data and adds it to the Big Data to fully understand the deeper meaning of the data.
Note:
SAP HANA Vora was released in September 2015 and is available in the cloud or on-premise
There are many use cases for combining Big Data with Enterprise Data. Here are just a few:
SAP VORA Use Cases
● 360-degree customer marketing – Combine customer data with unstructured data from social media, e-mail, Web site activity, and discussion forums to better target sales and marketing
● Cell phone service improvement – Analyze instances of poor cellular service, such as dropped calls or poor audio, by drilling from billing data to detailed call log data
● Confirm diagnosis with collected literature – Bring together patient data with up-to-date journal and medical literature data in real time to improve diagnoses and treatment plans
● Fraud detection – Detect anomalies and rogue trades by analyzing historical trends and current data simultaneously
● Risk mitigation – Perform Monte Carlo simulations to produce distributions of possible outcome values with more precise context
● Predictive maintenance – Optimize maintenance of transformers and low tension devices through more complete historical information
● Virtual power plants – Forecast consumption and production based on weather, load profiles, and so forth, with better context
● Analytics – Perform powerful analytics for infrastructure optimization energy theft detection, load balancing, and more
● Archiving – Keep archived smart meter, billing, supervisory control and data acquisition (SCADA), and customer relationship management data at the ready but a lower cost.
● Network capacity planning – Analyze call detail records (CDRs) and network load to plan infrastructure expansion with greater precision
● Real-time bandwidth allocation – Steer traffic and optimize network quality of service (QoS) in real time to maintain the best service quality
● Targeted network maintenance and upgrades – Analyze the impact of cable network congestion on churn, and identify which network upgrades will produce greater incremental revenue
● Insurance and Medicare fraud analysis – Analyze vast bodies of collected claims material to uncover fraud.
Airline maintenance planning — Combine aircraft sensor data collected in flight with flight
Note:
To learn more about SAP HANA Vora please refer to the SAP course HA500 — SAP HANA Vora
LESSON SUMMARY You should now be able to:
● Describe how SAP HANA Vora enables BI over Big Data
Unit 4: Data Provisioning in SAP HANA
Learning Assessment
1. What are typical characteristics of replication?
Choose the correct answers.
X A Virtualization X B Transformation X C Real-time X D Batch
X E Synchronization
2. SAP SLT can be used for real-time replication from SAP and also non SAP sources.
Determine whether this statement is true or false.
X True X False
3. SAP HANA EIM includes which components?
Choose the correct answers.
X A SDI X B SDA X C SDS
X D SDQ
4. What are some of the features of SDA?
Choose the correct answers.
X A Automatic data type translation X B Data cleansing functions
X C Evaluation and execution of push down possibilities
5. Which are correct statements relating to flat file loading?
Choose the correct answers.
X A The new table always has a 1:1 mapping between the file and table columns X B The supported file types for upload are: .csv, and .txt
X C When loading new data in a table that already contains data, the new data is appended to the existing data
X D The import function does not allow the renaming of columns changes to the data type for existing columns
6. Which are true statements?
Choose the correct answers.
X A SAP HANA Vora replaces Apache Spark X B SAP HANA Vora requires SAP HANA platform X C SAP HANA Vora provides OLAP features to Big Data
X D SAP HANA Vora combines Big Data and enterprise data for analysis
Unit 4: Learning Assessment
Learning Assessment - Answers
1. What are typical characteristics of replication?
Choose the correct answers.
X A Virtualization X B Transformation X C Real-time X D Batch
X E Synchronization
2. SAP SLT can be used for real-time replication from SAP and also non SAP sources.
Determine whether this statement is true or false.
X True X False
3. SAP HANA EIM includes which components?
Choose the correct answers.
X A SDI X B SDA X C SDS X D SDQ
4. What are some of the features of SDA?
Choose the correct answers.
X A Automatic data type translation X B Data cleansing functions
X C Evaluation and execution of push down possibilities X D Data recovery services due to power outage
5. Which are correct statements relating to flat file loading?
Choose the correct answers.
X A The new table always has a 1:1 mapping between the file and table columns X B The supported file types for upload are: .csv, and .txt
X C When loading new data in a table that already contains data, the new data is appended to the existing data
X D The import function does not allow the renaming of columns changes to the data type for existing columns
6. Which are true statements?
Choose the correct answers.
X A SAP HANA Vora replaces Apache Spark X B SAP HANA Vora requires SAP HANA platform X C SAP HANA Vora provides OLAP features to Big Data
X D SAP HANA Vora combines Big Data and enterprise data for analysis
Unit 4: Learning Assessment - Answers
HANA
Lesson 1
Describing the Types of Applications you can run on SAP HANA 144
Lesson 2
Connecting SAP Business Intelligence Tools to SAP HANA 149
Exercise 5: Create a Report with SAP BusinessObjects Analysis for Microsoft Excel 155
Lesson 3
Outlining SAP Business Warehouse on SAP HANA 163
Lesson 4
Describing SAP HANA Data Warehousing Foundation 167
Lesson 5
Describing the Basics of XS Applications 171
Exercise 6: Write Data into SAP HANA Using an XS Engine Application 173
Lesson 6
Describing the Purpose of the Business Function Library 179
UNIT OBJECTIVES
● Describe the types of application you can run on SAP HANA
● Connect SAP Business Intelligence Tools to SAP HANA
● Outline how SAP BW leverages SAP HANA
● Describe SAP HANA Data Warehouse Foundation
● Describe the basics of XS applications
● Describe the purpose of the Business Function Library