BBBT

Numerous business trends, accelerated by COVID-19, are rapidly driving the adoption of graph databases and analytics around the world. As the leader in Graph Database Technology, Neo4j will update BBBT attendees on the customer-demanded shift to graph in the cloud. The organization will also highlight innovative new use cases of graph technology in analytics, which are helping organizations overcome the challenges presented by the global pandemic.

Smart. Flexible. Anywhere. SAS Visual Analytics delivers an easy-to-use visual discovery and self-service analytics platform that supports the entire analytics lifecycle – from data, discovery to deployment. With SAS Visual Analytics, users can uncover relationships in data from across multiple data sources, create and share interactive reports and dashboards to drive faster, smarter decisions.

Legal & Ethical Data Analytics | Modern Access & Privacy Controls

The benefits of cloud analytics are enormous, empowering organizations to deliver insights faster than ever before while also reducing costs. Despite the strong upside, the migration of analytics workloads to the cloud has slowed - the result of an increasingly complex landscape of regulations intended to protect the privacy of data subjects. This has exposed data teams to new levels of risk when managing sensitive data and has resulted in a fear of litigation for violating regulations like GDPR, CCPA, HIPAA or a variety of rules such as employment laws, third party data use contracts, SOC-2 compliance, and others.

These pressures are daunting, but they don’t have to be. New architectural requirements are emerging in the personal data era that can safely scale data access for analytics in the cloud, while reducing legal and ethical risks.

Driving Time to Value for Machine Learning Deployments

Productionizing Machine Learning requires a different set of IT infrastructure and workflows than traditional software development. Algorithmia solves this challenge by offering an Machine Learning deployment and operations management platform. Algorithmia Enterprise provides an abstraction layer that connects and manages your models, data, compute resources, and inference to applications—think of it as an operating system for Machine Learning. We strive to provide the fastest time to value for Machine Learning with a platform which programmatically optimizes each ML model deployment while providing the some of the best and most comprehensive security and governance capabilities available, while integrating with your existing data science tooling, workflow and infrastructure resources. Our goal is to accelerate the realization of the value of your Machine Learning investment.

Teradata Update

Teradata will present a general update on Teradata Vantage, Teradata Vantage Customer Experience and a look into future plans. You will also learn about recent customers wins with a focus on several new cloud customers.

OmniSci has demonstrated the massive scaling possible using GPUs and CPUs for computation and visualization. Modern processing capabilities have opened up a whole new era of accelerated analytics at massive scale. While not every analytics problem requires massive scale, all users need tools that are properly sized for problems throughout their enterprise. This presentation will outline how OmniSci can visualize and query billions of rows of data on a single data science workstation or at a larger scale in our enterprise edition for servers on premises or in the cloud.

OmniSci experts will deep dive into our accelerated analytics platform to demonstrate industry specific use cases and demos, show how to deploy Jupyter notebooks with OmniSci, and how OmniSci makes analytics instant, powerful and effortless for everyone.

Neo4j: Graph databases & graph analytics

The Neo4j team will provide a brief introduction to graph databases, share typical use cases and explain why graph analysis is emerging as the data scientist’s not-so-secret weapon.

The webinar will start with an overview of some of our use cases to highlight Toucan’s positioning in the market, why our clients invested in the product, and how it changed the way they work. We will then go through the company’s vision and promise whilst bringing forward industry insights and challenges, and how we address them. This will be followed by a demo of a finished product (a Toucan dynamic app), and the Toucan Studio, which will take our viewers through the Toucan methodology and process through which they set up and deploy and app following our guided framework and embedded user experience. We will finish with the roadmap of the product and what 2020 will represent for us.

The Denodo Platform: A Logical Data Architecture for the Digital Age

In today’s digital age, fast, agile access to data is a competitive advantage. And yet, many organizations still struggle to unlock the value of their enterprise data because it is isolated in disparate formats, locations, and platforms. The Denodo Platform is a high-performant, real-time, and secure logical data layer – a “data fabric” – that provides integrated business views and catalogs of the underlying disparate data siloed across the enterprise.

Enterprises are shifting quickly from a world of raw data collection to automated decisions and artificial intelligence. Research shows that data has become the success factor for digital transformations. Organizations embracing a data culture with advanced analytics are 5x as likely to make faster decisions than peers and 2x as likely to be in the top quartile of financial performance. Data catalogs are increasingly at the center of enterprise-wide data culture initiatives. They are aggregating and automating data context – combining technical, business and social metadata into proactive recommendations to data consumers. Companies like MunichRe, Pfizer and GoDaddy, that adopt a data catalog enterprise-wide increase analytic productivity, drive information stewardship and promote broad analytic collaboration that delivers new products and services.