Denodo Datafest 2017

The optimizer is one of the most complex parts of any big data engine; it must ensure that the execution engine is performing at its best, so understanding how it works is crucial.

Finding the right data within seconds is what matters most to analysts and decision makers. Data virtualization incorporates a rich business-user oriented information catalog and self-service interface to search, discover, model and collaborate.

A discussion on the theme of why self-service BI is the future from our experts panel at Denodo DataFest 2017.

A discussion on the theme of how in-memory fabric redefines analytics architectures from our experts panel at Denodo DataFest 2017.

A discussion on the theme of the evolution of data virtualization from data federation from our experts panel at Denodo DataFest 2017.

Organizations are empowering business users with actionable intelligence derived from data-in-motion, data-at-rest, and enterprise applications. Edge computing plays an important role in the IoT ecosystem since immediacy enables faster response to urgent conditions.

Business users come in all shapes and sizes. It’s imperative to understand who they are (e.g., data analysts, power users, executives or machines) and the data they need. Self-service initiatives can only be successful when business users’ views of the data are holistic, and consistent across distinct business functions.

Speed is everything. Businesses that move fast leave their competition in the dust. But one needs high performance architecture to enable it.

Watch this Denodo DataFest 2017 session to discover:

Businesses are demanding more autonomy from IT to enable the creation the necessary reports and to perform analysis.

Every single item on a company mission statement relates to data at some level. It is from the position of data expertise that the mission will be executed and company leadership will emerge.

Modern data integration relies on fast data strategy the ability to quickly make the data available to the business users in real-time.

Today's complex organizations will often have hundreds if not thousands of data repositories, distributed across on-premise stores and now the cloud. For data to become truly democratized, non-specialists and data natives need to be able to easily find and access data without requiring outside help.

Big data projects are becoming mature and consistent. However, they remain siloed compared to the enterprise data. In addition, now new streaming data needs to integrated as well.

How productive would it be to create a universal semantic model that every reporting tool can use? This presentation will present such an approach to simplify support for any type of reporting tools.

As part of BARC's BI Trend Monitor 2018, 2,770 companies were asked to rate the importance of 20 trending topics. In this session, we will present the key factors for gaining value from data today.

Organizations are fast adapting cloud to lower the IT costs, and increase agility.

Microservices is an advanced architecture for rapidly building applications using a suite of loosely-coupled modular services.

Data lakes is a great solution for storing tens of thousands of data sets for statisticians to perform their daily functions. But how do you make that data available in a format that makes sense to them?

A discussion on the theme of logical data warehouse as the future in data warehousing from our experts panel at Denodo DataFest 2017.

A discussion on the theme of big data analytics and edge computing from our experts panel at Denodo DataFest 2017.

A discussion on the theme of big data analytics and edge computing from our experts panel at Denodo DataFest 2017.

Companies that move fast, stay one-step ahead of the competition and avoid being gobbled up. Keeping this law of the jungle in perspective, companies are modernizing their data architectures with real-time data delivery capabilities.

When processing very large amounts of data at the speed of thought, performance questions raise their ugly head. Logical data warehouse architectures rival the conventional data warehouses in speed while reducing the need to extract, transform, and load the data.

No time like the present! That's one reason why edge analytics continues to grow in value and importance. With the right analytic architecture in place, companies can not only identify opportunities at the edge, they can take appropriate actions.

Healthcare organizations are constantly challenged with delivering high quality care while complying with strict regulations. Erasmus University Medical Center required the agility to quickly deliver BI products for its business users.

Fast Data is an absolute business need – it requires the access to the most up-to-date data in real-time to perform its business function best and be ahead of the competition. At Altus Analytics, the faster we can turn around the data, the faster we can accelerate the generation of revenue.

Today’s digital economy demands a new way of running business. Flexible access to information and responses in real time are essential for outpacing competition.

Which technologies increase real-time data delivery? Database and other technologies are taking on support for in-memory fabric to further boost the speed of data delivery in this impatient world.