Tag: On-Premise BI / Analytics

As technology stacks expand and transforms over-time, one constant shines bright: the need for metadata. Metadata manager tools have come and gone over the years, but they always felt incomplete. But now we have Oracle Enterprise Metadata Manager, the world's first complete metadata tool. In this session, we'll examine this recently released product and see…

Raise your hand if you've heard this: "It takes too long to deliver new content with Oracle Business Intelligence". While in practice this statement is basically true, the goal of this presentation is to prove that it doesn't have to be. Continuous Integration is the practice of integrating, testing and deploying automatically as part of the…

The 4 top trends in technology right now are mobile, in-memory, cloud, and big data but the one that can add the most immediate business benefit is big data. Do you want to know, "what does big data actually mean?"  We'll define it then get to a much more important question: how can I actually…

Big Data insight is getting tremendous attention across all organizations but data mining and analytics are not new methodology. This presentation emphasizes on how big data technologies are helping data discovery and turning information and knowledge into wisdom. This presentation will not only help understand different types of analytic techniques using examples but also explain…

Analyzing data reservoirs in the brave new world of big data can be very challenging and time-consuming. What if you could quickly and easily apply sophisticated analytical functions to any data—whether it’s in Hadoop/NoSQL sources or an Oracle Database instance—using a simple declarative language you already know and love? Welcome back to SQL! This presentation…

As Business Intelligence systems gets more integrated in today’s businesses many businesses find that they need more complex questions answered. The simple questions such as sales by customer within a region over time are now easy to answer. But now companies want to ask questions about how many unique purchasers do they have on their…

Learn how to apply Machine Learning methods for the tasks of database administration like anomaly detection, classifying various database events as well as SQL and PL/SQL code. We will use example operational events from the database like alert.log, listener.log, trace files as well as common database performance statistics.

Join us for lunch, and what promises to be a lively and informative conversation with IBM's Chuck Calio as he dives into the next generation of IT Growth solutions, including Cloud, Analytics, Big Data, Mobile, and Social. You'll walk away with new and innovative ideas on how you as an Oracle professional, can take advantage…

Organizations are quickly moving beyond the definition of big data and are starting to implement it in the organization. Understanding the future of big data is crucial in the early stages of decision-making for big data architectures. This session lays out Oracle’s roadmap and strategy for the enterprise big data platform of the future. Specifically,…

Big Data offers many opportunities for large enterprises to improve competitiveness and to create new, data-driven products. And it offers significant opportunities for IT professional career growth. But these opportunities to not come without risks for the individual and organization. Big data is potentially transformative for some industries and those that cannot or will not adapt may face extinction. Furthermore, big data projects are inherently ground breaking and while many will prevail and lead to fame and glory for the big data pioneer, others will suffer ignominious defeat.

In this presentation we’ll look at the market forces driving big data, drill into the key technologies available to power a big data project and outline the attribute that allow big data projects to succeed.

After assessing the business imperatives that are driving big data projects we will survey the big data technology landscape which includes technologies such as the Hadoop ecosystem, Exadata, Machine Learning, collective intelligence and predictive analytics. We'll conclude with recommendations on how to optimize your big data project, career and architectures.