Talend

With ever increasing volumes and varieties of data forming the basis of our analysis universe, Machine Learning promises to help automate and condense cycle time to actionable insight. But how can you overcome the stubborn complexities of adoption associated with this subset of Data Science?

In this on-demand webinar see how Talend helps its data-driven customers embrace and exploit Machine Learning capabilities faster and more efficiently than traditional, coding-based approaches.

In this on-demand webinar you will learn about:

- The challenges of generating insight from data
- Principles of machine learning
- How to train, test and operationalise Machine Learning solutions using Talend
- How other Talend customers are exploiting Big Data solutions

In this on-demand webinar, Google and Talend experts demonstrate how to implement machine learning algorithms into analytics pipelines, and extract sentiment analysis to achieve a new level of insight and opportunity.

A strong data governance program ensures that you have the policies, standards, and controls in place to protect data effectively and access it for decision making. Data governance may become one of the most important functions of your data integration architecture when it comes to data agility.

Talend and MapR break down the steps for turning a data lake into a data hub with appropriate data management and governance activities: from capturing and reconciling personal data to providing for consent management, data anomyzation, and the rights of the data subject.

GDPR has major implications for the IT landscape of every business. Companies are shifting away from data silos and closing down shadow IT to create a governed personal data hub and data services.

In this webinar we demonstrate how to achieve the 5 pillars of data management for GDPR compliance with a practical example: matching 3rd party consent data to existing records with appropriate data governance.

See how easily you can put the pieces together:

Data capture and integration into a data lake
Data cleansing, loading and matching
Self-service curation and certification
Data classification and lineage using metadata manager

Critical inhibitors and best practices for data lake success

What critical inhibitors put your data lake project most at risk? Learn why data lakes fail and how to achieve success using the power of cloud.

It's no surprise that massive amounts of unstructured and semi-structured data provide a wealth of information about the state of your business. Clickstreams, sensors, social media, and weblogs generate huge datasets that can be analyzed in a data lake, as long as that data lake is part of a scalable big data analytics infrastructure.

In this session, we show you how to put your data lake on the path to success. Topics include:

- Why data lakes fail
- Key enablers of a successful data lake project
- Agile DevOps practices for faster time-to-market
- Why a multi-cloud strategy is critical
- Incorporating governance and security into your data lake