Smart Infrastructure & Smart Applications for the Smart Business – Infrastructure & Application Performance Monitoring
Data Warehouse Automation & Real-time Data – Reducing Time to Value in a Distributed Analytical Environment
2-3 December 2019 – Residenza di Ripetta, Rome, Italy
For many companies, data and analytics are now considered strategic to business success. It’s key to their digital transformation processes and to become Data-driven. So much so that major investment is going into Big Data and Analytics at the moment as a matter of urgency and many companies are under pressure to deliver value quickly.
At the same time, the thirst for new data to analyse is growing rapidly. New data is pouring into the enterprise and new analytical workloads have emerged. However, with so much activity going on, many companies are struggling with the complexity that new data and new analytical workloads have caused. Different types of data store have emerged both on-premises and in one or more Clouds.
The number of different data sources is growing and new analytical algorithms, libraries and tools are appearing in addition to new analytical platforms. And if this was not enough, wave after wave of new technology still keeps emerging in areas like Data Science, data streaming, new database products and Cloud native platforms.
The result has been that many companies are trying to progress but have ended up with a fractured and siloed data and analytical setup. Gartner indicated that 60% of all big data projects fail. So:
- How do you sort this out?
- How do you become Data driven?
- What should your data strategy be?
- How do you put data to work?
- How does this impact on your data architecture?
- Should you move away from batch to streaming data flows or somewhere in between?
- How do you govern and deliver trusted data in a Big Data environment? Should you create a Data Lake and a Data Lab?
- And with so much now happening on the Cloud and in database technology do you need Hadoop any more?
- Can you now build a Big Data system using SQL technology?
All of this will be answered and more at this year’s Italian Big Data Conference.
- Becoming Data driven – A data strategy for success and business insight
- Putting Data to work for business success
- Big Data Architectures – Optimising your data architecture to match your workload
- Being successful with Data Lakes and a Data Lab
- Implementing Data Governance in a Big Data Landscape – Data Catalogs, Business glossary, Data Discovery, Policy Management
- Can you build a Big Data system with SQL?
- Data Streaming – New data architectures from Batch to Lambda to Kappa
- Guidelines for migration your Big Data Warehouse to the Cloud
- Data Quality, Big Data and Data Warehouse – not yet a marriage made in heaven