Programma lezingenzaal 4

4

Datamanagement is een van de belangrijkste dingen waar data scientists en data-engineers zich dagelijks mee bezig houden. En gegevensbeheer wordt alleen maar belangrijker! Maar datamanagement is geen rocket science en ik zal je laten zien waarom niet!

PROGRAMMA LEZINGENZAAL 4

Woensdag 14 september Alex van Wijnen Solution Specialst

11:45 - 12:15

THE IMPORTANCE OF INTEGRATION AND DATA MANAGEMENT FOR BIG DATA USE CASES

Big Data provides business with immense opportunities to gain insights in customer behaviour, or ways to improve operations. To enable rapid adoption of use cases and handle the ever increase variety, velocity and volumes, companies need to focus more on integration and data management.

Erik Assink

Managing Director, North America

12:45 - 13:15

PRORAIL'S STORY ON GETTING MACHINE LEARNING READY!

The perfect case for image recognition, right? That is what we did! Implementing something delegate as deep learning in a rough and wild industrial environment has its challenges. In this talk we share what we tried and learned to make it work!

Job Wegman

Product Owner

Clint de Keizer

Machine Learning Engineer 13:30 - 14:30

HOW IS SPAR UNLOCKING BUSINESS VALUE THROUGH ADVANCED DATA ANALYTICS?

SPAR is the world’s largest voluntary food retail chain, founded in The Netherlands in 1932 and now comprises over 13,600 stores in 48 countries around the world. To stay updated on trends, market conditions and product performance, SPAR analyzes data shared by their retailers. This session will cover how by using Designer cloud powered by Trifacta, SPAR is able to turn data challenges into a competitive advantage for their business.

Dharshini Manoharan Bhuvaneswari

Business Data Analyst

Sri Madhavi Kanna

Data Analyst 14:45 - 15:15

DATA DEMOCRATISATION: HOW EVERYONE CAN BENEFIT FROM ACCESSIBLE DATA THAT PAVES THE WAY FOR IMPROVED MARKETING OUTCOMES

Data democratisation fundamentally changes the way we work. In this session you will learn how it benefi ts modern marketing and fi nd out:

James Alty

Managing Director and Founder

15:30 - 16:00

PRESENTATIE VEEAM

16:15 - 16:45

ADD VALUE TO YOUR DATA USING S3 – AKRIVVERKET – NORWEGIAN PUBLIC DIGITAL ARCHIVE.

Collecting, scanning, and indexing all Norwegian public documents, books, pictures, and more from over 100 years ago to the current day. Arkivverket´s role in Norway is to make information and data easily available to the public. “Legacy storage protocols with external uncoupled metadata databases are no longer surfactant”.

Ole Petter Johnsen

COME JOIN US AT INSPIRE EMEA!

17-20 October 2022

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Register now for €200 discount

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Vertica is a deploy-anywhere SQL database designed for advanced analytics, speed, and elasticity. Here are a few of the ways Vertica can put your analytics team at the top of their game:

Built-in Machine Learning Vertica offers more than 650 built-in analytical functions, as well as builtin machine learning algorithms. Vertica supports cluster-optimized ML algorithms, R, and Python. Data scientists and analysts can build their models using their preferred tools and languages, then leverage Vertica to power them on bigger data sets. They can import models built and trained in other platforms and languages—like TensorFlow, Spark, Python, and SPSS—via the PMML (Predictive Model Markup Language) format. Vertica’s algorithms support classification, clustering, and predictive applications. These include linear regression, logistics regression, k-means, naïve Bayes, support vector machines, and random forest.

Hybrid Cloud Support Vertica can be deployed via SaaS, public clouds, private clouds, Kubernetes, and bare metal deployments – or any combination of these – to provide analytics when and where you need it. Vertica runs on popular public clouds, including Google Cloud Platform (GCP), Azure, AWS, Alibaba, and VMware clouds. You can also use a similar configuration on-premises to leverage a range of local object stores, such as Apache Hadoop HDFS for communal storage, MinIO, VAST, Dell ECS, Scality, H3C, and Pure Storage.

Separation of Compute and Storage Vertica separates the computational resources from the communal storage layer of your database. This can greatly reduce the cost of analytics performed in the cloud, since cloud vendors universally charge much more for compute than storage. Teams can spin up compute nodes as needed, then spin them down to reduce costs.