Jupyter notebooks are transforming the way we look at computing, coding and problem solving. But is this the only “data scientist experience” that this technology can provide?
In this webinar, Natalino will sketch how you could use Jupyter to create interactive and compelling data science web applications and provide new ways of data exploration and analysis. In the background, these apps are still powered by well understood and documented Jupyter notebooks.
They will present an architecture which is composed of four parts: a jupyter server-only gateway, a Scala/Spark Jupyter kernel, a Spark cluster and a angular/bootstrap web application.
Now that the Data Science hype is levelling out, many companies are wondering what went wrong as they could not extract values from their data science efforts.
In this webinar we will explore what does it take to apply data science and machine learning in the real world.
Key takeaways include:
- How can you go beyond the traditional data warehouse when doing machine learning
- How should you adapt your processes to keep monetizing on your data
- How to close the feedback loop between your customers and your machine learning models
- What kind of profiles are essential to successfully become a data driven organization
Data science is a domain which promises to convert the available data in actionable insights. This could translate in huge wins for the organizations both in financial terms (higher revenues, reduce costs) but also in terms of better services for the customers with more tailored products and a personalized and improved customer experience.
But how to get those results out from the initial intuitions of statisticians and scientists to the customers? What is the best way to translate those solutions in production-level APIs and services? How to asses the quality of data-driven algorithms? These are very concrete concerns for anyone who wishes to operationalize data science into data-driven products.
This webinar will describe a number of techniques and patterns to monitor and deploy data models and to stay in control of predictive, data-driven services.
Leading pharmaceutical manufacturers and clinical research organizations are investing in digital operations across the development and commercialization spectrum to improve efficiency, accuracy, and trust when bringing new products to market.
Watch this on-demand webinar to hear from digital trailblazers and adopt best practices to ensure that your organization is collaborating effectively and building a safe global trust network for digital success.
Topics covered include:
• Applications for digital transactions and signatures
• Identity management
• High impact regulated use cases
• Compliance with global and industry regulations
• Best practices for digital adoption
Watch and learn how Documentum Research and Development (R&D) and Documentum Submission, Store and View (SSV) ensures alignment with global regulatory guidance to speed submissions.
Listen as Lena Shafir, Product Manager, Life Sciences Regulatory Solutions, provides an overview of recent enhancements to Documentum Research and Development (R&D) and Documentum Store and View (SSV). She’ll also cover how our latest release (4.2) delivers lifecycle support for medical device documentation and ensures alignment with global regulatory guidance to speed submissions.
Good data is the key to innovation, solid research collaboration, and, ultimately, the creation of life-saving drugs and treatments.
But does your IT strategy reflect this? All too often, data is compromised and constrained by the needs of your enterprise’s applications. Join our webinar to discover a new data-centric approach to IT that's radically changing the biggest names in life sciences.
By moving to a data-centric model, your organization will be better poised to:
•Integrate data regardless of source, volume, and variation
•Quickly and easily change out applications
•Uncover unique insights
Gary Palgon, CISSP and VP, Healthcare and Life Sciences at Liaison, will demonstrate how to apply this innovative data-centric approach in a life sciences environment.
Join this live roundtable to learn about data science from a wide variety of angles, from the infrastructure to the visualization.Read more >
Big Data and Data Science are multi-faceted concepts. In all of their guises, they are driving revolutionary changes in nearly all social, public, and institutional settings. One of most significant and far-reaching developments is the democratization of Data Science. Now everyone and every organization is "doing it".
In this presentation, I will describe some of the most prevalent characteristics and concepts surrounding the current activities associated with Data Science. I will then describe the importance of Data Science as a research discipline and as an application methodology for making advances in Big Data Analytics.
Following the discussion of these concepts (steps toward making discoveries from Big Data), I will then describe some of the misconceptions (missteps on the road to discovery) that can afflict current Big Data efforts.
Over the past eight years, Trulia has amassed a number of huge datasets related to real estate, geography, and the activity of its users. We have successfully built out our data science team with the goal of turning this data into new product offerings and improved monetization.
This talk with look at our decisions in assembling this team, including what the core competencies should be and tradeoffs between engineering and analysis skill sets. We will also look at the projects the team has undertaken.
In an age when blockbusters are few and far between, pipeline acceleration and performance are the key to bottom-line profits. Where will you find the immediate savings you need in time and money?
Watch this on-demand webinar to learn 10 ways to reduce cycle time and development costs with a fully digital solution. Topics covered include:
-Top life sciences use cases
-21 CFR Part 11 capabilities
-Best practices for digital adoption
-Global scalability and compliance
-Industry and validation partners
For companies operating online, web speed and performance always impact business outcome. As Cyber-Monday approaches companies are looking to maximize conversion and revenue. Part two of SOASTA’s “Easy Data Science” series illustrates how data science provides a real-time competitive advantage. We’ll show you “how.”
Join Mat Ball and Iris Lieuw for a tech-talk on how SOASTA data science provides your company a competitive advantage.
The talk will showcase SOASTA’s data science capabilities for the following outcomes:
The most accurate alerting for campaigns or heightened periods of traffic, modeled from your entire user-event history
Real-time visibility into user session paths, allowing marketing and development teams to quickly identify and remediate slow loading pages critical to campaign revenue
Remedy poor user engagement, site slowdowns, and capitalize on revenue opportunities with total visibility across all of your dimensions (OS, Browser, Device, Geo, etc.)
For online retailers and media players, performance means business. Using Data Science helps companies gain a competitive edge with respect to customer experience, IT performance, and business outcome. The question is, “how?”
Join Mat Ball and Iris Lieuw for a tech talk on how SOASTA data science can give your company a competitive advantage in your market.
The talk will showcase SOASTA’s data science capabilities, but will also provide a glimpse into how e-commerce and media players are using data science for the following:
- Biz-Ops, combining marketing and performance analytics to maximize marketing campaigns in real-time
- Efficient webpage prioritization for IT workloads and Senior Management Visibility
- Getting the most accurate alerting based on your entire user event history
The second part of the two-part series on the US Federal Life Sciences market focuses on the two of three EMC pillars: IT Transformation and Trust. The architecture and infrastructure that has powered the faster-than-Moore's-Law growth in Life Sciences, specifically Genomics will be presented along with Trust. Trust, and not technology is the singular issue that will determine the progress of Genomics into the practice of Precision Medicine.Read more >
Fueled by the life-changing technologies of genomic sequencing, genotyping, gene expression analysis, and bioinformatics, Life Sciences organizations are experiencing intense growth in data. Life Sciences researchers are generating massive amounts of data with storage retention requirements from two years minimum to perpetuity. The technologies and tools driving biomedical research and drug development such as next generation sequencing (NGS), genomic analysis, proteomics, and high content screening (HCS) also pose immense challenges to managing data throughout the data lifecycle - from generation, to analysis, to archive.Read more >