Analytics Big Data SAP

Take a Leap from Big Data to Big Value with SAP HANA 2.0

By: | Suresh Suravarapu

Publish Date: June 30, 2017

SAP HANA is a game changer when it comes to data processing and analytics.
Data Modeling is the core of HANA application development. Primarily , Data Modeling is a fusion of both ETL ( extract , transform, load ) technology and business processes. It helps the transformation of disparate and normalized data into an organized structure suitable for reporting and decision-making. The main function of Data Modeling task is to deliver quality and consistent access to data. This exercise results in building a data mart or data warehouse.
 
Without these processes, Business Intelligence for organizations will be anything but intelligent. Failing to implement a strong data foundation will fail to deliver meaningful analytics.
 
SAP HANA modeling helps to create rich views and multi-dimensional analytics of data. It has the ability to aggregate, analyze, calculate, compare and forecast enormous volumes of data at speeds unlike any currently available database in the market. Here is a peek into HANA 2.0 Modeling features:

  • New modeling environment: SAP Web IDE for SAP HANA (Web IDE*)
  • New Calculation View modeling features
  • New CDS graphical modeling features
  • CDS views vs. Calculation Views: Which one to choose in which scenario
  • Data Masking
  • Set Operations
  • Multiple Selection Handling
SAP HANA Data Modeling

Data modeling views are created on top of database tables along with implementing business logic to generate meaningful reports. By using Java, HTML based application or even SAP HANA native applications the modeling views can be consumed. Third party tools like MS Excel can also be used to link with HANA to create reports.
Enhanced performance at runtime by modeling views is achieved by implicit use of optimized SAP HANA In-Memory calculation engines. To get the most out of SAP HANA the SAP views need to be modeled. The views are categorized into:

  • Attribute Views:

    It represents master data and can be used to join to a dimension or other attribute view. These are highly reused and shared in the other two views.

  • Analytics Views:

    Designed specifically to execute star schema queries this view leverage the computing power of SAP HANA to calculate aggregate data.

  • Calculation Views:

    Used on top of the above two views, the calculation views are composite views. It can perform complex calculations.

DATA-LAKE
HANA2.0 Enhancements
Database Enhancements
  • Enable load balance read-intensive operations between a primary and secondary instance of SAP HANA with the active / active-read.
  • Automate orchestration of HA/DR processes with enhanced SAP Landscape Management integration.
  • Optimize workload for 3rd party backup tools by consolidating SAP HANA log backups.
Administration Enhancements
  • Manage one instance, multiple tenants or 1000’s of SAP HANA instances within the SAP HANA Cockpit administration and monitoring tool.
  • Prevent run-away queries and manage system thresholds with enhanced workload management.
  • Reduce time and cost when implementing change by capturing, comparing and analyzing multiple workload replays.
Advanced Analytical Processing Enhancements
  • Search:

    Improved searching and filtering on dates. Dynamic search rules help to detect duplicate data. Batch mode search run can check a large number of records in a single call.

  • Text Analytics:

    Easily embed natural language processing into company’s products with a new native SQL interface. Text analysis is possible for all languages including ones using space between words. Manage domain-specific custom dictionaries and rules within the Web IDE for SAP HANA.

  • Graphic Data Processing:

    New visualization enables more efficient and faster graph data analysis. Leverage existing Cypher query language skills for Cypher for pattern matching.

  • Predictive Analytics and Machine Learning:

    More pre-packaged algorithms helps to create richer predictive applications. Parallel processing across large-scale partitioned data can run-scoring functions faster.

The intent of this blog is to provide some insights and approaches to the HANA modelers, which can be helpful when they start working on the solution design and development.

Suresh Suravarapu S4 HANA, BI Analytics, EIM, BIBO, BI Consultant @YASH Technologies
For More Information Download SAP HANA Services Brochure

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