Key Research Findings: How to Optimize Business Processes
Based on recent research by analyst Bob Larrivee of AIIM, this webinar will address how organizations can leverage technology to identify, evaluate and optimize business processes to increase operational efficiency.
Join us as we explore:
- Drivers for problem-solving, tracking KPIs, process failures and workflow management
- How technology can reduce errors and exceptions that lead to lost business and non-compliance
- Increasing visibility to optimize processes, reduce costs and deliver a superior customer experience
RecordedFeb 26 201553 mins
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Natalino Busa, Head of Applied Data Science at Teradata
AI to Improve Regulatory Compliance, Governance & Auditing. How AI identifies and prevents risks, above and beyond traditional methods. Techniques and analytics that protect customers and firms from cyber-attacks and fraud. Using AI to quickly and efficiently provide evidence for auditing requests.
Machine learning and cognitive computing for:
-Process and Financial Audit
-Data computing systems
-Tools and skills
Merav Yuravlivker, Co-founder and CEO, Data Society
Is it worth it for companies to spend millions of dollars a year on software that can't keep up with constantly evolving open source software? What are the advantages and disadvantages to keeping enterprise licenses and how secure is open source software really?
Join Data Society CEO, Merav Yuravlivker, as she goes over the software trends in the data science space and where big companies are headed in 2017 and beyond.
About the speaker: Merav Yuravlivker is the Co-founder and Chief Executive Officer of Data Society. She has over 10 years of experience in instructional design, training, and teaching. Merav has helped bring new insights to businesses and move their organizations forward through implementing data analytics strategies and training. Merav manages all product development and instructional design for Data Society and heads all consulting projects related to the education sector. She is passionate about increasing data science knowledge from the executive level to the analyst level.
Ani Manian, Head of Product Strategy, Sisense and Philip Lima, Chief Development Officer, Mashey
So you’ve decided you want to jump on the data analytics bandwagon and propel your company into the 21st century with better analytics, reporting and data visualization. But to get a BI project rolling you usually need the entire organization, or at the very least the entire department, to get on board. Since embarking on a BI initiative requires an investment of time and resources, convincing the relevant people in the company to take the leap is imperative. You’ll need to construct a solid business case, defend your budget request and prove the value BI can bring to your organization.
In this webinar you’ll discover:
- Why organizations need to invest in BI to begin with
- How are organization deriving value from BI
- How to build an internal business case for investing in BI
- What are the intricacies of how to build a budget
- How to drive your company to a purchasing decision
- How to start realizing value from BI now
Natalino Busa, Head of Applied Data Science at Teradata
The best services have one thing in common: a superb customer experience. Banking services are no exception to this rule, and indeed the quest for an effortless, well informed, and personalized customer experience is one of the main goals of today's innovation in digital banking services.
According to what Maslow has described in his "pyramid of needs", customers are seeking a more intimate and meaningful experience where banking services can actively assist the customer in performing and managing their financial life. Predictive APIs have a fundamental role in all this, as they enable a new set of customer journeys such as automatic categorization of transactions, detecting and alerting recurrent payments, pre-approving credit requests or provide better tools to fight fraud without limiting legitimate customer transactions.
In this talk, I will focus on how to provide better banking services by using predictive APIs. I will describe the path on how to get there and the challenges of implementing predictive APIs in a strictly audited and regulated domain such as banking. Finally, I will briefly introduce a number of data science techniques to implement those customer journeys and describe how big/fast data engineering can be used to realize predictive data pipelines.
The presentation will unfold in three parts:
1) Define banking services: Maslow's law, modern vs traditional banking
2) Examples predictive and personalized banking experiences
3) Examples of data science and data engineering pipelines for banking and financial services
Lonny Northrup, Sr. Medical Informaticist – Office of Chief Data Officer, Intermountain Healthcare
Hear first hand from one of the nation’s leading healthcare providers, Intermountain Healthcare, on what is actually being accomplished with big data and machine learning (cognitive computing, artificial intelligence, deep learning, etc.) by leading healthcare providers.
Intermountain has evaluated between 300 and 400 big data and analytic solutions and actively collaborates with the other leading healthcare providers in the United States to implement the solutions that are delivering improved healthcare outcomes and cost reductions.
Matt Davies, Head of Marketing EMEA, Splunk, & Sebastian Darrington, EMEA Director, Big Data & Analytics Solutions, Dell EMC
Leveraging Big Data and Analytics to create actionable insights.
Splunk & Dell EMC will share insights into the challenges & opportunities customers are seeing in the market – with the ‘needs to’; reduce costs and improve efficiency within IT (operational analytics), improve Compliance (security analytics) & implement Shadow IT due to the business not receiving the right service from IT. CIO Priority is keeping the lights on and so on…
Dell EMC & Splunk combined strengths are helping numerous organizations to ‘leverage Big Data and Analytics to create actionable insights’.
Natalino Busa, Head of Applied Data Science at Teradata
Today, data is everywhere. As more data streams into cloud-based systems, the combination of data and computing resources gives us today the unprecedented opportunity to perform very sophisticated data analysis and to explore advanced machine learning methods such as deep learning.
Clouds pack very large amount of computing and storage resources, which can be dynamically allocated to create powerful analytical environments. By accessing those analytics clusters of machines, data analysts and data scientists can quickly evaluate more hypotheses and scenarios in parallel and cost-effectively.
The number of analytical tools which is supported on various clouds is increasing by the day. The list of analytical tools spans from traditional rdms databases as provided by vendors to analytics open sources projects such as Hadoop Hive, Spark, H2O. Next to provisioning tools and solutions on the cloud, managed services for Data Science, Big Data and Analytics are becoming a popular offering of many clouds.
Analytics in the cloud provides whole new ways for data analysts, data scientists and business developer to interact with each other, share data and experiments and develop relevant insight towards improved business processes and results. In this talk, I will describe a number of data analytics solutions for the cloud and how they can be added to your current cloud and on-premise landscape.
High performance and scalable data mapping offers unlimited opportunities for quickly categorizing and identifying key insights for retail, defense, insurance, utilities, natural resources, social sciences, medicine, public safety and more.
Organizations, already awash in customer data, know geospatial capabilities can put a new “lens”on existing reports. Data from smartphones, GPS devices and social media has organizations anxious to factor in customer location, origin or destination, with time or day.
Join IBM Product Marketing Manager David Clement and IBM Senior Product Manager Rick Blackwell and explore the new, world-class mapping and geospatial capabilities for IBM Cognos Analytics and Watson Analytics. Discover how you can add geographic dimension to visualizing critical business information in reports and dashboards in Cognos Analytics.
Traditional report factories are rapidly becoming obsolete. Enterprise organizations are shifting to self-service analytics and looking for a sustainable, yet long-term approach to governance that satisfies the needs of both the business and IT.
The Business needs real-time access to data to drive critical decisions. IT needs to audit and manage data to ensure it’s accurate, secure, and governed to scale.
With only eight percent of people in traditional organizations able to both ask and answer their own questions, it’s time to take a closer look at your analytics strategy.
Join this webinar to take a closer look at enterprise analytics and learn how:
· Visual data analysis brings speed, value, accuracy, collaboration and leads to culture of analytics
· Modern enterprises are eliminating boundaries between IT and the business
· Shifting to enterprise self-service analytic tools empowers both the business and IT
Listen to our interview at Big Data LDN with Jez Clark, Co-founder and Director at Eden Smith.
Jez will share insights focused on the importance of Big Data & Data Science skill both for employers searching for talent and professionals seeking opportunities.
For those looking for these skills:
-How big is the talent pool? Which skills are in the pool? What are the common job titles and themes?
-How do you attract the talent and what are the challenges?
For those looking for opportunity:
-How can you manage expectations -- opportunities at Facebook/Google vs smaller SMEs
-The majority of those in data science are not commercially aware, how do we fix this?
-Data scientists don't know how to behave for a client to secure opportunity -- what are some tips to help?
-How do you position yourself and showcase transferable skills?
Listen to our interview at Big Data LDN with Justin Mullen, Co-founder at Datalytyx.
Justin will talk about:
-Relevant use cases for businesses who need to know how to go about deployment
-Key capabilities needed for deployment and the right tools to make things easier
-The definition of a modern data architecture
Jeff Kato, Taneja Group, Jeff Cobb, Qumulo, Nick Rathke, SCI
Computer users aren’t top data producers anymore. Machines are. Raw data from sensors, labs, forensics, and exploration are surging into data centers and overwhelming traditional storage. There is a solution: High performance, massively scale-out NAS with data-aware intelligence. Join us as Jeff Cobb, VP of Product Management at Qumulo and Taneja Group Senior Analyst Jeff Kato explain Qumulo’s data-aware scale-out NAS and its seismic shift in storing and processing machine data. We will review how customers are using Qumulo Core, and Nick Rathke of the University of Utah’s Scientific Computing and Imaging (SCI) Institute will join us to share how SCI uses Qumulo to cut raw image processing from months to days.
Jeff Kato, Senior Analyst & Consultant, Taneja Group
Jeff Cobb, VP of Product Management, Qumulo
Nick Rathke, Assistant Director for IT, The Scientific Computing and Imaging Institute (SCI)
Ina Yulo (BrightTALK), Andrew Davies (Fiserv), Martin Koderisch (Edgar Dunn)
Predictive Analytics and the study of Big Data has helped many institutions to detect fraudulent practices before they become a hazard to the business. This is especially evident in the Financial Services sector where deploying an efficient prevention and detection strategy is of utmost importance.
Join this panel where experts will discuss:
-Which analytics to look at to stop fraudulent payments in real-time
-Using trends and behavioural analytics to detect anomalies
-How to implement a holistic strategy that's right for your organisation
-The challenges in maintaining compliance standards
-Use cases and applications of analytics to prevent financial crime
David Burden - CEO, Daden Limited, an immersive learning and visualisation company
This webinar will look at the challenges currently facing VR across a variety of "serious business" use cases from education and training to data visualisation and what the technology needs to do in order to get beyond the "wow" and move into being a productive, useful and truly in-demand technology.
Listen to our interview at Big Data LDN with Jason Foster, Director & Founder at Cynozure.
Jason will discuss:
-The value of Big Data and which skills are required to deliver that value
-How to get started with Big Data projects
-What to do if progress is limited
-Business opportunities around customer insight, supply chain analytics, and more
Jennifer Riggins, Dave Russell (Hortonworks), Michael Bironneau (Open Energi), Alex Montgomery (Microsoft)
Rapid data growth from a wide range of new data sources is significantly outpacing organizations’ abilities to manage data with existing systems. Today’s data architectures and IT budgets are straining under the pressure. In response, the center of gravity in the data architecture is shifting from structured transactional systems to cloud based modern data architectures and applications; with Hadoop at it's core.
Join this live and on-demand video panel as they discuss how the landscape is changing and offer insights into how organizations are successfully navigating this shift to capture new business opportunities while driving cost out.
Bobby Gill (Data & Digital Analytics Director at The Economist) and Sebastian Fabri (Analyst at Looker)
Listen to our interview at Big Data LDN with Bobby Gill (Data & Digital Analytics Director at The Economist) and Sebastian Fabri (Analyst at Looker)
The duo will discuss a successful case study on data-driven decision making.
They will tackle:
-How to implement data solutions quickly and efficiently in the cloud
-What are the challenges of data-driven decision making?
-How to discover data pain-points across an organisation and solve these accurately
-The importance of real-time analytics in generating actionable insights
Adrian Whitehead (Specialist SE) & Stefan Radtke (CTO Isilon). Dell EMC
The technology landscape is moving at a fast pace and organisations are struggling to keep up and need to think of new ways of processing, analysing and getting value from the vast array of data sources now available.
Tune in to listen to a conversation between two technology experts who discuss the current challenges experienced in the big data industry and what tools and infrastructure are being deployed including Spark, Hadoop, Splunk etc. to get value from the massive amounts of data flowing around the globe!
Andy Cotgreave, Technical Evangelist, Tableau Software
Listen to our interview at Big Data LDN with Andy Cotgreave, Technical Evangelist at Tableau Software.
Andy will discuss:
-Moving beyond dashboards and applying the “5 Whys” technique to data
-Best practice tips for exploring and manipulating data
-The need to think about “data exploration” as a task in itself, but as part of a person’s goal to make an impact on their business
Joe Hellerstein, Chief Strategy Officer at Trifacta
Listen to our interview at Big Data LDN with Joe Hellerstein, Chief Strategy Officer at Trifacta.
Joe will answer:
- As the founder of Trifacta, tell us a bit about your company and just what is data wrangling?
- How does it differ from ETL?
- You have just announced a new server edition of Trifacta, can you tell us more this?
- Can you give us some examples of how your customers are leveraging Big Data?
- What makes a big data project successful?
- What advice would you give to companies starting out with a big data project?
- What are the biggest hurdles to overcome?
- What use cases are the most prevalent at the moment and will that change over time?
Managing and analyzing data to inform business decisions
Data is the foundation of any organization and therefore, it is paramount that it is managed and maintained as a valuable resource.
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