The availability of data (IoT/Geospatial/Logs/Social), new generations of technology (Hadoop/AI/Machine Learning), and a cultural shift toward data-driven decision making continue to drive demand for Big Data and Analytics. The International Data Corporation (IDC) predicts that the worldwide revenues for big data and business analytics will grow from €121 billion in 2016 to more than €186 billion in 2020.
Big Data four V’s
This figure shows the importance of getting into the world of Big Data in order to stay competitive on data-driven decision making. As traditional BI mostly focuses on “simple” representations of traditional business processes, Big Data and Analytics allow you to go wider and dig deeper in data using Artificial Intelligence/Machine Learning techniques such as Regression, Classification, and Clustering algorithms – see our Machine Learning introduction blog.
Putting Hadoop in place
In order to understand where SAP Vora fits in the Big Data landscape, it’s important to understand what Hadoop is. Check out our Hadoop introduction blog here for in-depth information about this.
Setting up Hadoop/Vora as a separate platform is the first step towards a Big Data architecture. By setting it up as a separate platform, its options and possibilities can be explored without interfering the company’s “traditional BI” environment. When you feel confident about using the platform, the integration options of Vora can be used to leverage the “traditional BI” as well.
There are multiple ways to deploy Hadoop.Cloudera, MapR and Hortonworks are known for delivering enterprise ready Hadoop installations all supporting SAP Vora. With the acquisition of Altiscale, SAP is making the Hadoop Cloud more accessible with SAP Cloud Platform Big Data Services.
SAP Cloud Platform Big Data Services services feature the key capabilities for Big Data – Apache Hadoop, Apache Spark, Apache Hive, and Apache Pig. They also support third-party applications like H2O, Alation, AtScale, and more. The services are equipped with Vora and always up to date with the latest production-ready releases.
SAP Cloud Platform Big Data Services
But what is SAP Vora?
To simplify, SAP Vora serves two generic functions:
Making Data Exploration/Data Science and modeling more intuitive and accessible on top of the Hadoop platform.
Allows integration of Hadoop data and Vora models with SAP HANA.
The following picture illustrates the SAP Vora architecture as an independent Big Data platform:
SAP Vora architecture
In the first place SAP Vora allows you to start with Big Data in a more “Traditional BI” way, meaning easy creation of tables and views such as star schemas while at the same time having the direct visualization options at hand. Modeling in Vora looks a lot like modeling in SAP HANA.
The integration possibilities allows you to fetch data virtually without having to physically move it using SDA (SAP HANA). Also, you can fetch data from SAP HANA so it works in two directions.
SAP Vora and HANA integration options
SAP Vora allows customers to easily combine business data from traditional BI environments with data from IoT, clickstream, logging, social, and other sources that have been saved in Hadoop.
New features in SAP Vora 1.4
There are several improvements with SAP Vora 1.4. The modeler is updated with a new landing page, support for Graph engine, and DocStore. Also, visualizations for Views are present, you can now build complete Analytical models and validate them using “Data Preview”. There is support for Import and Export of Views, which simplifies the transport of tables/models across different systems (Dev-QA-Prod). Vora 1.4 also adds support for “star joins” when creating views, this enables connecting a central fact table with other dimension data.
SAP Vora 1.4 modeler screen
On the integration side Vora in-memory Relational tables are now supported. Vora views can be consumed through HANA using voraodbc. Once HANA Wire is enabled, HANA Studio or Web IDE can be used to create Virtual Tables on Vora and join that with SAP HANA.
New/updated features in Vora 1.4:
Next Generation In Memory Engine featuring Vora Native Distribution (DQP)
Voraodbc – Access from HANA
Supports now In-Memory Engine
Supports Kerberos Authentication
Visualization: Charts for Relational Data, Graph and Time Series
Export/Import of Views
Support for Partition Function/Schemes
Improved Load Speed 6x-10x
Faster data recovery on failure
Faster Query Execution
In order to stay competitive as a company, data-driven decision making is key. With Vora, SAP is facilitating tools to gain even more insight on the continuously increasing data requirements.
The Next View can help in the E2E Big Data solution. Together with the Design Thinking Center, we can help you investigate the data-driven journey and integrating Hadoop/Vora in your business.
https://www.nextview.nl/wp-content/uploads/2018/01/nextview-logo.svg00nextviewhttps://www.nextview.nl/wp-content/uploads/2018/01/nextview-logo.svgnextview2017-05-02 20:24:442018-01-17 09:01:53SAP Vora 1.4: The big data picture
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