Name: What Does It Mean to Be Data-Driven and Why Should You Care? Series 3:Technology
Start: 2023-01-17T11:00:00Z
End: 2023-01-17T11:00:31.000Z
Location: BrightTALK
Rating: 5

Learn about AWS data, analytics, and AI/ML best practices from AWS Partners. Understand how to execute a modern, agile approach to analytics in the cloud for your organization. Through presentations, deep dive sessions, and demos, you will learn how AWS Partners can deliver AWS-based solutions and services so you can access deeper insights, simplify infrastructure management, and accelerate operational analytics.

In today’s economic conditions, frugality is king. When it comes to data architecture, that means every element is carefully selected to provide the greatest value for the lowest cost. In this webinar, we’ll look specifically at how organizations can leverage serverless business intelligence (BI) tools to save costs while tapping into powerful analytics and artificial intelligence capabilities.
 
As the first BI tool built on the cloud, Amazon QuickSight integrates easily with your entire data ecosystem, including a growing suite of analytic capabilities from services such as AWS Glue and Amazon SageMaker – without the licensing and infrastructure costs we’ve all come to expect. It is now possible to make the shift to serverless BI quickly, easily, and for low cost with automated conversion technologies, such as the BI Converter developed by Wavicle Data Solutions. Not interested in spending your hard-won BI budget on a multi-year BI migration project? No problem.
 
Join analytics experts from AWS and Wavicle Data Solutions as they explore how a frugal data architecture can deliver easier access to low-cost data visualization, leaving more funds to pursue artificial intelligence capabilities that enable predictive and prescriptive analytics. 

In this webinar, you’ll learn:
- How serverless BI uncomplicates your architecture
- How Amazon QuickSight and the Wavicle BI Converter can accelerate your shift to serverless BI
- How serverless BI can pave the way to predictive and prescriptive analytics capabilities
- Analytic trends that are shaping new business intelligence expectations

Reduce costs and improve analytics with serverless BI

Patient engagement refers to digital health initiatives that allow patients to fully participate in healthcare, support positive behavior change, and facilitate better comprehension of diagnoses and treatment plans as suggested by their providers. 

With the rise in digital health and mobile applications, interactions between patients and service providers have increased exponentially, facilitating dynamic real-time exchange of healthcare data with clinicians. Apexon focuses on digital first solutions powered by Amazon Web Services to improve patient experience across the care continuum leading to better health outcomes, patient compliance, and ultimately a higher quality of life.

Enhancing Patient Engagement With AWS

Three industry challenges conspire to reduce the reliability of data-driven insights in life sciences and pharmaceutical organizations:
• Inefficient methods for measuring marketing campaign performance
• The perceived high cost of new analytics solutions
• And a lack of United Semantics to drive artificial intelligence.

However, you can overcome this confluence of factors to unlock indispensable analysis to meet client expectations and deliver faster time to market by 40%. But, how?

Tune into this webinar to examine how Infosys’ platform provides a single source of truth for faster insights, adaptability for persona-specific marketing, and scalability through deep dive analytics using AWS Cloud Native technology.

Unlock Adaptable Analytics for the Pharmaceutical Industry with Infosys

Discover how modern data warehouses can improve access to data and provide seamless analytics for petabyte-scale datasets. In this webinar, we discuss:

○ The challenges posed by traditional data warehouses, and how Data Warehouse
Modernization can help.

○ Customer Story: A global machinery company's end-to-end modernization journey
facilitated by Quantiphi.

○ Setting up a roadmap to build a modern data warehouse with Amazon Redshift.

Modernize your Data Warehouse with Amazon Redshift

The commercial infrastructure of life sciences organizations is complex with data living in multiple systems across multiple functions and often locked in vendor systems (e.g. CRM). This creates challenges for availability and accessibility to unleash and democratize actionable insights. Organizations have invested significantly in commercial data lakes to solve this challenge, but still lack a foundational data layer, an Intelligent Commercial Insights Foundation (ICIF), to enable a connected data ecosystem and analytics tools to support various commercial use cases. 

In this webinar, experts from AWS and ZS will share how they have partnered to develop a globally ready commercial data foundation that enables cross functional data liquidity and interoperability. This domain-infused, tech-driven modern solution provides the agility and flexibility to quickly connect data lakes for accelerated time to value.  

Register today to learn: 
- Best practices for leveraging an AWS microservices architecture to accelerate implementation of a commercial data lake-in-a-box solution for timely insights generation. 

- How to accelerate the implementation of a robust data management system that can help streamline the process of accessing and analyzing data. 

- How to expedite the setup of ingestion and analytics pipelines through reusable templates, rich pharma business rules and data quality checks. 

- How to seamlessly integrate accelerators to quickly solve common data management challenges and enable advanced commercial use cases across sales, marketing, value and access, and more.   

- How to futureproof business use cases through a modern cloud architecture based on automated AWS elastic and serverless components to provide global scalability while optimizing IT spend.  

- How to build foundations to enable better analytics democratization and scalable deployment of machine learning and artificial intelligence.

Accelerate Decision Making in Commercial Life Sciences

Organizations have a requirement to implement data governance due to the presence of PII, PHI, and PCI elements; the process of sharing and operationalizing data movement becomes an involved task as it must encompass data governance and data security and include audit capabilities.

But changing and building on the existing data movement processes is a manually intensive process and not only increases in time to process, but also loses its agility as the lag between the transactional applications and the analytical downstream warehouse increases. The result is that the business making decisions using the analytical data is not as accurate and well-informed, and adds direct, measurable cost through manual validation and audit.

Explore in this webinar the more modern data transformation solution that LTI has introduced to customers, with checkpoints introduced at various stages — including manual interventions — that operationalize the data movement across different AWS accounts using native AWS services for a well-architected and well-governed process.

Cross-Account Data Sharing Made Simple: AWS Automation for Improved Governance

In the past decade, as cloud solutions have been gaining acceptance into the Healthcare IT environment, imaging systems have been part of the early adopters of public cloud services. The transition from onsite imaging environments to cloud has been challenging to implement and adopt into daily workflow. In turn has created a perceived negative impact on the imaging workflows and ultimately the patient care with lags and delays in accessing the studies. Many hospitals are still hesitant to transition their medical images either partially or entirely into a cloud environment. There are various reasons for this hesitancy but largely the key reason is the need for high availability and the inherited lag-time in retrieval of image files from cloud.

Join our webinar to learn about -

· CitiusTech’s collaboration with AWS to launch Amazon HealthLake Imaging service to address key challenges around latency and data access

· Complexities of networking and integration of medical images with EHR data
· Various complexities and considerations in migrating medical images into cloud environment
· The importance of harvesting and standardizing data from all sources during a patient journey
· Driving organizational strategy across your medical imaging enterprise with analytics and data management

CitiusTech is a leading provider of digital technology and consulting services to payer, provider, medical technology, and life sciences companies. With over 8,000 healthcare technology professionals worldwide, CitiusTech powers healthcare digital innovation, business transformation and industry-wide convergence for over 130 organizations, through next-generation technologies, solutions, and products.

Enterprise Medical Imaging: Moving from Onsite to Cloud

U.S. payers are working to improve care management, but it can be difficult due to limited tools and a need for timely access to specialized data that is not necessarily available to them. Payers are shifting from traditional call center care management to a modern and flexible platform-based care management approach. Data is being leveraged more effectively to send personalized, targeted messages to members.  

In this webinar, we’ll discuss opportunities to: 

·         Leverage data sources that are commonly overlooked 
·         Create customized digital solutions 
·         Enable care management with a high level of personalization to increase engagement 
·         Improve care compliance and enhance disease prevention 

Cloud adoption and data analytics are key to integrating siloed data and truly engaging members, as is choosing the right healthcare data platform. During this webinar, you will learn about Human360®, powered by AWS, a nimble platform with flexible component architecture.  

As an AWS Healthcare Services Competency Partner, we’ve helped our clients optimize operations, improve member experiences, and accelerate their journey to the cloud using AWS’ solutions for more than 14 years. Join us to explore how to improve the ROI on your care-management program while ensuring a healthier experience for members.

Cut through the chaos: How to use untapped data for personalized care management

Join us for part one of this three-part series where we will discuss the challenges keeping companies from being data-driven. We will cover the following:

Series 2: Culture
We will be discussing three topics in creating a company data culture: organisational design, democratisation, and critical thinking. 

Organisational design will be around the topic of centralised vs. de-centralised models. How to de-centralise data by treating it as a product and centralise the ownership of the platform. 

Democratisation of data is about giving people access to more data, but also giving them the chance to act and be empowered to act on that data. 

Critical thinking is about having a culture of diving deep and looking for the story behind the data that is being served by the platform.

What Does It Mean to Be Data-Driven and Why Should You Care? Series 2: Culture

In this shapeshifting and fast-paced environment, generating actionable insights out of data is more critical than ever. Let us take you through our transformation journey that has helped hundreds of clients extract more value from their data. Learn how our clients develop the ability to make market-leading data-driven decisions and how we are helping them.

Reinventing Your Businesses with Data

Join us for part two of this three-part series where we will discuss the challenges keeping companies from being data-driven. We will cover the following: 

Series 1: Strategy In this webinar, we will level-set concepts used in the next two sessions. We will address three topics: components, examples, and focus. 

- What are the main components of a solid data strategy? Who defines them and what are the roles of each executive stakeholder? 
- We will bring examples of companies that aligned their goals with this strategy and vice versa to make this chapter more concrete. 
- Companies that go from quick in, to quick win, lack the focus in their strategy that will allow it to be persistent across several leadership changes. These companies will usually define a strategy, stick to it for a year, and then start over again. Culture is how a data strategy becomes pervasive beyond the times and provides a guiding light that aligns with a long-term strategy.

What Does It Mean to Be Data-Driven and Why Should You Care? Series 1: Strategy

With over 64 Zettabytes of data created in 2020 alone, businesses are facing unprecedented challenges in data management. Traditional warehousing solutions are not built for the volume, veracity and variety of data today’s organizations are generating. With next generation, cloud based solutions, Amazon Web Services is empowering businesses to meet these challenges with infinitely scalable, highly available tools. 

Learn about working with an AWS Partner like Red Oak Strategic to leverage Amazon Redshift to help your organization future-proof its data warehousing infrastructure and empower teams with unmatched automation and analysis.

Big Data Challenges and Solutions with Amazon Redshift and Red Oak Strategic

Campaign-2-Closure (C2C) is an AI driven Marketing and Campaign analytics solution.

It enables data-driven Omni-channel Customer Experience, Optimized Inventory Management & Order Processing. C2C’s Channel Optimization Personalization feature offers visibility over consumer footprint and customer’s buying propensity.  It provides speed & agility that sustains change for events or anomalies like COVID-19 & holiday demand and is empowered with Dynamic Customer Campaigns and Forecast Demand / Predict Change.

Key takeaways: Learn how

- An end-to-end marketing campaign can be implemented using a data-driven approach.
- By injecting customer feedback into systems and using it for machine learning, marketing campaigns can be made intelligent and allow for faster campaign closure 
- You can deliver superior customer experiences and better business outcomes
- AWS Data Driven Everything (D2E) program and how it can help

Campaign to closure – A Data Driven Everything approach

The promise of data mesh for Federal government organizations is significant, and most stand to benefit from pivoting from their current approach to a data mesh as soon as possible. Today, most Federal government organizations want to drive innovation and become data-driven, and they are not afraid to make huge investments in technology to try and achieve aspirational data goals.  Many have invested billions of dollars in machine learning/artificial intelligence (ML/AI) capabilities to support the use of data analytics for data-driven decision-making, yet they are still struggling to source, manage, access, and protect trustworthy analytical data at scale.  As a result, most are not realizing maximum value from their significant and increasing investments in data analytics, and their data value to investment ratio is low.  This disappointing Return on Investment is not due to an absence of high-level support within the organization.  In fact, in most federal agencies, it is the Chief Data Officer (CDO) or leaders at the highest levels of the organization pushing for the change needed to accelerate innovation and realize data advantage.  The reasons for failure share common patterns, requiring a nudge to a new approach that is grounded in lessons from distributed architecture, microservices, and product thinking.  In this webinar, you will learn:

1.           What is Data Mesh?

2.           Why Do Federal Organizations Need Data Mesh?

3.           Why Be an Early Adopter?

4.           How to Design a Data Mesh Platform

5.           How to Get Started with Execution

 
Speakers:

*Cindy Walker, VP, Data Services CoE Lead, Octo 

 *Rohini Krishnapura, Senior Technical Product Manager, Amazon Web Services

Data Mesh: Why Federal Agencies Should Be Early Adopters

Consumer behavior is changing rapidly, and is causing a huge impact on the retail industry. Consumers have numerous choices at their fingertips for making their purchase decisions. It is very important to provide the right product to the right people at the right time for creating a winning strategy. Retailers not only need to focus on attracting repeat business from customers but also understand their needs to keep them loyal to their brands. Timely customer insights from the most recent product engagement, sales and purchasing behavior data is very critical to be successful. 

In this webinar, learn how easy it is to load sales data into AWS data lake and quickly generate customer insights using a variety of reports and visualizations with Amazon QuickSight. We will also demonstrate one-click data ingestion, understanding Amazon QuickSight and its capabilities, dashboard creation, specific visualizations and reports most appropriate for analyzing Retail data, and how managers can utilize them to create a winning data strategy.

Quickly Turn Retail Data Into Customer Insights Using Amazon QuickSight

When your company needs a fast, easy-to-use, cloud-powered business intelligence (BI) solution to build data visualizations, perform ad-hoc analysis, and obtain business insights from your data, CDW and AWS deliver. Empower decision-makers with secure, visual, interactive dashboards without teams of data engineers spending months building complex data models. Amazon QuickSight empowers users with deeper application insights, enabling them to perform advanced ad-hoc analysis with natural language queries and leverage machine learning capabilities. While utilizing Embedded Analytic in conjunction with QuickSight, organizations can drive monetization opportunities to everyday applications.

Better business intelligence: How cloud and ML elevate analytics maturity

Join us for part three of this three-part series where we will discuss the challenges keeping companies from being data-driven. We will cover the following:

The biggest call to action here is about the necessity of technological decisions to withstand the pressure of marketing messages, open-source trends, and shiny new tools. This usually leads to inconsistent architecture and a high effort of integration. 

Integration is a challenge on its own, so decisions don’t need to make it worse by balancing the choice between the best tools for the job and an effort to integrate with the current state. 

Lastly, we will address skills and how most things are transferable, but new tools make it harder than it needs to be.

What Does It Mean to Be Data-Driven and Why Should You Care? Series 3:Technology

Machine Learning

Data strategy

Data

Data Governance

Data Lake

Data Science

Data Analysis

Data Integration

Data Visualization

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What Does It Mean to Be Data-Driven and Why Should You Care? Series 3:Technology

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Data & Analytics Modernization | AWS Partners