Name: How To Operationalize Data Science Projects
Start: 2019-04-04T03:00:00Z
End: 2019-04-04T03:00:44.000Z
Location: BrightTALK
Rating: 5

Looking for the latest information on Big Data, the Internet of Things (IoT), Data Integration, and Predictive Analytics? Then join our channel to hear from industry thought leaders, Pentaho customers, and Hitachi Vantara experts as they discuss everything from how to turn data into valuable insights with embeddable analytics to how to accelerate value with Hadoop, NoSQL, and other data sources.

Your SAP S/4HANA Transformation Journey may include some critical decisions that can impact your path to overall value attainment. Regardless of where you are in the journey, it is not too late to adjust and influence your project outcomes in a positive way. Reducing technical debt, embracing new capabilities, and welcoming artificial intelligence can be exciting, challenging, and even stressful for any team adopting new innovations as part of their shift to S/4HANA. 

In this session, we will provide some insights into five key project planning decisions which can reduce project execution risks, address organizational change management concerns, and simplify strategies for future upgrades. Our goal is to equip you and your team with tangible recommendations to allow intentional focus on your transformation objectives. This session will build your confidence and allow a check on the credibility of your detailed roadmap to the intelligent enterprise.

Five Key Decisions to Fast Track your SAP S/4HANA Transformation Journey

In the rapidly evolving landscape of cloud computing, mastering the management of Azure workloads necessitates a strategic approach that prioritizes resilience, cost efficiency, and security. The Hitachi Application Reliability Center (HARC) stands as a beacon, blending cutting-edge frameworks, and purpose-built facilities to deliver unmatched cloud workload management capabilities. This webinar serves as your guide to understanding how HARC methodologies can revolutionize workload management within Azure, with a specific emphasis on resilience, cost optimization, and security.
 
Explore the core pillars of HARC and its seamless integration with Azure's ecosystem. From fine-tuning Service Level Objectives (SLOs) to implementing error budget policies, observability, resilience engineering and establishing robust cost optimization measures, we'll delve into actionable strategies to optimize workload management on Azure.

Elevating Azure Cloud Workload Efficiency through HARC

The SAP Business Technology Platform (BTP) is a key component for your transformation journey. As you plan to modernize your solution landscape, knowing the essential BTP components will prove helpful. This session will provide a high-level overview of the value that BTP offers to automate business processes, integrate systems, accelerate application development, and provide advanced data and analytics capabilities. Growth and innovation must be intentional and sustained based on thoughtful and enlightened decision making. 

This session is for you if any of these questions seem familiar:
1. Are you struggling to understand how to overhaul your core business processes, eliminate technical debt, and incorporate new features and functions to increase efficiency?
2. Do you want to keep your core solution “clean” and take advantage of new capabilities to optimize critical operations?
3. Are you hearing all the buzz words, but are not quite sure of the relevancy for your technology decisions? 
4. Are you curious and want to accelerate your learning curve?

Key takeaways:
1. Provide clarity on what BTP is and what it is not
2. Share our understanding of how BTP should be positioned in your landscape
3. Help your team understand the art of the possible through BTP
4. Understand how BTP helps to support “Clean Core Concepts”

Unpacking SAP BTP: Shaping your strategy for growth and innovation

Join this webinar to explore how you can ensure flexibility, reliability, and accelerated delivery for your data with Pentaho in hybrid cloud environments while scaling easily, staying agnostic and keeping code changes to a minimum. Our solution architect will answer questions such as: Which deployment model to choose? Will it adapt to my cloud vendor? Should we migrate to the cloud completely or remain hybrid? What about Kubernetes and Docker?
Find out which Pentaho building blocks are the best-fit combination for your organizations’ requirements. We will talk you through the decision-making process by way of three distinct ETL use cases.

DataOps Deep Dive: Pentaho in the Cloud - DI and BA Deployment Models

The compliance and regulatory needs of financial institutions are constantly evolving, driving the adoption of artificial intelligence (AI) and other powerful tools to detect and prevent risks such as fraud, money laundering, and cyberattacks with greater efficiency and effectiveness. To do this, it is crucial to utilize high-quality, trusted data that is fit for purpose. This is accomplished through the rapid discovery and classification of data, as well as the continuous automation of quality assessment.

Your takeaways:

- What are the technology trends in financial services
- How to successfully automate compliance
- Data discovery and classification for AI modeling
- Continuous data quality assessment
- Strategies for increased cyber resiliency
 
Register and join us at this webinar replay and delve into the intersection between technology and compliance in financial services. Also examine the latest trends and developments that are reshaping the industry.

The Intersection of Technology and Compliance, Trends in Financial Services

Hybrid clouds comprise data, computing, and software applications that span from on-premises IT infrastructure to private and public clouds. There is a continual need for data to move, driven by data governance, sovereignty, and compliance, by cloud costs, and by cloud-based data analytic services. Data movement within hybrid cloud is an ongoing process that must be automated and managed. It's not a one-off, lift-and-shift data migration activity. Data needs to be maintained and remain fluid, available for analytic processing wherever and whenever needed. Tools to do this, in a sustainable fashion, are lacking in many organizations. 
Watch this webinar to learn about the state of the industry in hybrid cloud data management from 451 Research and Hitachi Vantara, where we share some advice on a process and solution for dynamic data migration for hybrid cloud and the savings and risk avoidance that it affords.

Continuous Data Migration in the Age of Hybrid Cloud

Are you getting the most out of your analytics investment? How do you measure success? 
In this DataOps Deep Dive webinar, we will explore the various methods of expanding the reach and increasing the adoption of your analytics applications. Pentaho has extensive methods to embed data and analytics into the workflow of your analysts and users. Looking to add a custom chart or visualization to use in your application? No problem. Watch our demo of the latest Pentaho 9.4 enhancements allowing detailed styling and branding of your visualizations. Tune in to see the potential of Pentaho!

Pentaho Business Analytics: Enhancing Adoption with Custom Styling and Embedding

Join this TDWI webinar and expert panel to learn more about where organizations are in their data management journey, their challenges and best practices for success. As organizations strive to keep up with increasingly complex data and enhance their analytical capabilities, they often need to transform their data management practices. TDWI has observed that many organizations are migrating to the cloud or already have hybrid models in place that involve both on-premises and cloud platforms. Some are utilizing cloud data stacks to manage and store their data, while others use a data fabric strategy to integrate data across multiple environments, both on premises and in the cloud. Evolving an organization’s data management strategy, however, is a journey. The journey involves organizational transformation, architectural adjustments, infrastructure changes, and new data governance approaches.

The State of Data Management

The convergence of IT and OT has become increasingly vital, and CIOs play a crucial role in ensuring its success. Leveraging OT and integrating it with IT business data can accelerate digitalization and increase agility and adaptability. Data convergence is essential and involves utilizing front-office software and enterprise data to meet site operations requirements. Conversely, IT may need to adopt new tools to gather OT data and integrate it with business data for analysis and automation across departments.

Utilizing a unified data management solution can streamline the process, saving time and expenses while providing better operational awareness and outcomes.

During this webinar, we will explore a cutting-edge data management solution that seamlessly integrates edge (OT) and operations/business (IT) data. This powerful tool organizes and blends data in ways that enhance operational awareness, providing businesses with valuable insights, information, and a platform for automation. By leveraging this solution, businesses can streamline their operations and make data-driven decisions that improve efficiency, reduce costs, and drive innovation.

Unlock Operational Efficiency with IT/OT Data Integration

Do you find that BI, data science, and support teams aren't able to find, or access, relevant data to do their jobs? Or maybe executives complain about a lack of data or distrust of data from operations. If end users are discovering that data sets are incomplete or out-of-date, then this session is for you.

Industrial organizations are generating more data than ever before and looking to institute analytic applications to transform their organizations and give them a competitive advantage. Next-generation Data Lakes can create business value by efficiently storing all OT data in a central location and merging it with IT data. Whether you are creating a Data Lake from scratch or adding and managing operations data as part of your existing enterprise data repository, this session will help.

Discover how to automate the entire process to collect and securely store data from all sources and manage unstructured data, time series, documents, photos, video, and more. An Industrial Data Lake is the single source of truth for all your operations data.

You will learn how to:
• Create a trusted and unified view of data across multiple operating sites and regions.
• Eliminate data silos, empower optimization decisions and enable other operations departments.
• Control big data costs, curate, and catalog your data and support self-service dataflow management.

Activate your Industrial Data Lake for Data Products

Automated trusted data discovery was central to State of Arizona’s sustainability initiatives— finding the right data from hundreds of thousands of water sources in a fast and secure fashion. To fuel this trusted data discovery, State of Arizona is leveraging Lumada DataOps - Data Catalog to make it easy for all the data consumers to find and leverage trusted quality data — exactly when they need it.
 
Join us as Lisa Williams, Manager of the Office of Enterprise Data Management for the Arizona Department of Water Resources and Kunju Kashalikar, Director Product Management at Hitachi Vantara discuss best practices around data discovery, profiling, search and quality using Lumada DataOps - Data Catalog to improve data discovery.

State of Arizona Accelerates Trusted Data Discovery with Lumada Data Catalog

Data management is critical to reliable, empowered, and faster decision-making in the energy & utilities industry. Integration and governance of data from multiple sources inside and outside the organization are needed to meet the demands of energy industry conversion for power generation and transmission. 

In this session, we will talk about the challenges of collecting, blending, and organizing data and how to overcome them with the backdrop of customer examples and what's happening in the field today. 

Attendees will learn: 
- Modern tools and techniques that can help with the process and drive success
- How to extract the value within your data for use in critical operations and planning decisions
- How to overcome the pitfalls in gathering and conditioning operational data
- How to make reliable, empowered, and faster decisions more consistently

Is Your Data Reliable and Complete Enough to Make Good Decisions?

The lack of new operator capability to run operations efficiently results in increased waste, lower productivity, and safety concerns. It is hard to hire skilled operators and supervisors which results in less production/maintenance capacity, slowing business down and reducing revenue. You want the ability to hire employees and have them functioning at the level of seasoned operators in weeks vs months using predictive and prescriptive analytics.

In this online seminar we will cover tools and techniques that will equip your team to get there more quickly and scale more broadly across your enterprise. This includes:
• Modern data connectivity and ingestion with minimal disruption to operations and systems
• Data prep including process tag name rationalization, time stamp alignment, etc.
• Leveraging Digital Twins for data modeling
• Training accurate and dependable ML applications for equipment
• APIs and embeddable dashboards for a unified HMI environment

Value Provided:
• A competitive advantage through the activation of company-specific data assets and processes
• Address large scale use cases in cost optimization and throughput; upstream and downstream plant optimization, examples: refining and chemicals, manufacturing production, water gathering and water distribution, customer demand and production

Bridging the Industrial Worker Knowledge Gap with AI and Digital Twins

Industrial organizations are generating more data than ever before and looking to institute AI and Analytic applications to transform their organizations and give them a competitive advantage, to control costs and optimize operations. Because DataOps is a new concept to industrial, there is a chasm in understanding between IT and OT teams that must be bridged to fully realize sustainable digital transformation for an industrial business.

As an Operations Leader, you understand the value of automation and operations management systems, but may struggle in the IT concepts and terminology that are more well known in commercial businesses such as banking, ad-tech, and insurance. You do, however, appreciate how a factory works and how well-designed production processes execute. Industrial DataOps is a lot like a factory production line in the way it automates, upgrades, improves, and assembles another valuable raw material which is, of course, data. In this session, we will explain Industrial DataOps in the context of the way a manufacturing plant is optimized. This will help to bridge the divide between the plant manager and the central IT manager, allowing the  understanding these techniques of professional data management to drive sustainable digital transformation. And also, we will share Lumada Industrial DataOps DEMO to share how we can help putting the data to work.

In this webinar, audience will learn
- How to bridge the divide between the plant manager and the central IT manager
- The techniques of professional Data management 
- Lumada industrial DataOps DEMO (Capabilities)

The Data Factory: Put the data to work

Data management is fundamental to every application. Managing this precious asset is an essential competency in modern businesses of every sort. Innovations in data platforms are being adopted, and data management approaches are evolving rapidly to keep pace. Increasingly, enterprises are converging their data warehouse, data lake, and other data management platforms onto distributed cloud-native infrastructures. As more types of data are consolidated into their platforms, enterprises implement more scalable DataOps pipelines and more comprehensive governance practices to manage it all. Want to learn more? This webinar brings together a panel of experts, moderated by James Kobielus, TDWI’s research director for data management. The panel will discuss the hotter trends in data integration, governance, and management, including:

- Increasing use of AI/ML for intelligent DataOps automation;
- Growing reliance of data governance, quality, and curation on centralized data catalogs;
- Adoption of cloud data marketplaces as the go-to source for reference data sets;
- Emergence of synthetic data as a supplement or replacement for source data in the MLOps pipeline;
- Team-oriented policy authoring and management within the data stewardship workflow;
- Democratization of data engineering through visual, low-code tooling; and
- Examples of what successful real-world organizations are doing today

Expert Panel: What's Ahead in Data Management in 2023

An SAP S/4HANA deployment can be a demanding, complex, and time-consuming project. SAP modernization, SAP database adoption, and SAP cloud migration together pose a challenge with too many variables for most businesses. Even with the wealth of support options available to businesses making the move to SAP S/4HANA not all succeed. Seeing these unsettling trends Hitachi Vantara has put together their best practices for an SAP modernization initiative. Join us to learn how Hitachi Vantara can assist in SAP transformation design, deployment, management, and migration to help you modernize your SAP environments quickly and effectively.

 

David Branson is a Global Partner Alliance Manager with Hitachi Vantara working closely with SAP to help customers achieve success with their SAP transformation initiatives. David has assisted numerous customers, consultants, and product teams to deliver digital innovation that unlocks SAP business value through the power of technology and partnership. Hitachi Vantara is a strategic partner with SAP that can maximize the return on your SAP S4/HANA investment. Make sure that you benefit from all SAP has to offer by partnering with a leading SAP solution provider like Hitachi Vantara.

Modernize your SAP environments quickly and effectively

You face a dilemma. The front office wants you to move faster than ever. But you need to supply more hard evidence to regulators to comply with constantly shifting requirements.

It’s time for a new approach—one that speeds up compliance while cutting risk.

In this webinar, we explore data and automation strategies to help you protect sensitive information and report accurately. Attendees will learn:
- New or complex requirements that may present hidden compliance risks.
- Common data management challenges and methods to overcome them. 
- Results from a survey of your peers in governance, risk, operations, and more.
- Best practices to meet regulatory requests quickly and accurately.
- Ways to integrate data seamlessly and get accurate information faster, with an enterprise data fabric.

Firm Foundation for Constant Change: Automating Compliance in Financial Services

Today’s data scientists use machine learning to predict trends, plan ahead of demand and events, and uncover patterns and behaviors. But they spend a significant amount of time on data engineering rather than actual data analysis, delaying the operationalization of machine-learning projects.

Find out how you can solve this challenge and help your data scientists be more productive. 

About our speaker:

Dr. Engin Cukuroglu is a data scientist at Hitachi Vantara, Singapore. He received his BS in chemical and biological engineering and has a MS and a doctorate in computational science and engineering. His studies primarily focused on data analytics and big data in protein-protein interactions. After getting his degrees, he analyzed genomic data and developed pipelines for cancer and stem-cell research. His findings have been published in peer-reviewed journals. 

Dr. Cukuroglu is currently working with rail operators, mining companies, manufacturers, banks, fleet operators and delivery partners in Asia-Pacific to enable their machine-learning and predictive-analytics strategies.

How To Operationalize Data Science Projects

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How To Operationalize Data Science Projects

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