Name: Modernizing Data Pipelines
Start: 2022-11-16T08:49:00Z
End: 2022-11-16T09:52:32.000Z
Location: BrightTALK
Rating: 4.5

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.

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

For industrial organizations with vast business processes to manage, the large variety of machinery across value chains often results in high operational costs. Inefficiencies, such as production delays, inclement weather that slows deliveries, and unexpected machine failures can lead to millions in lost revenue and increase the cost of doing business.

Analytics is the operational key to success. Minimize unscheduled downtime, optimize fleet activities, and improve customer experience by blending machine-generated internet of things (IoT) data with other contextualized data to feed predictive models. It may not be easy to do this across machines, lines, or plants, but there are tools that bring a simple no-code approach to help bring value quickly and easily through edge processing, helping you to overcome challenges and maximize return on investment. By hosting more applications and data management at the operating site level, cloud storage and compute costs can also be further optimized.

You will learn how to:
– Connect to machine data sources and perform univariate analytics like FFT, ML, and more at the edge.
– Streamline data pipelines, and quickly create custom data sets through automation.
– Machine learning orchestration makes data science teams more productive.
– Embedded analytics allows insights to be delivered at the point of business impact.

Analytics at the Edge - Moving Data Mgmt & Analytics Closer to Site Operations

The pursuit of business insights is a central focus of the enterprise. More than a natural resource, data is fueling strategic decision-making and, as a result, the future of business.

Discover why The Industrial Metaverse is built on a solid data fabric and how to get there.

The use case examples are built on a strong Industrial DataOps infrastructure and a data fabric that allows the integration, storage, cleaning, curation, and governance of data at the edge, core, and cloud levels.

Some of the Industrial/Business Metaverse use cases that will be covered during the panel are:
1. Product design and engineering
2. Hands-on training
3. Employee onboarding
4. Virtual services for hands-on work

The Industrial Metaverse is built on a Strong Data Fabric

Join us in this fireside chat with 451 Research and Hitachi Vantara on the State Of DataOps in 2022 and see how Enterprises are using intelligent DataOps to unify data, govern it, and deliver seamless customer experience.  Demystify the hype around data fabrics and see how DataOps can help you build your fabrics to deliver key business outcomes.  Learn how you can put data at the heart of decision-making with new AI-driven data management solutions.

Optimize Your Data Fabric for Digital Innovation

Learn how to deliver data to drive business decisions across your organization, regardless of where data resides using the latest capabilities of Pentaho 9.3 and hear about the latest data challenges organizations face today. See how moving from Pentaho Community Edition to Pentaho Enterprise Edition can provide comprehensive capabilities and long-term support that are essential for modern data management, integration, and analytics. Keep nimble and scale your data pipeline delivery in on-premise and hybrid cloud environments, including containerization across public clouds to deliver data easily, quickly and ready for your users.

Deliver Data into Decisions with Pentaho 9.3

In this interactive panel discussion, Harvard Business Review examines the roles of leadership, technology, and culture in building an optimal environment for creating and acting on data insights.

Discover how businesses can best position themselves to reap the rewards from DataOps with Alex Clemente, Managing Director, Harvard Business Review Analytic Services, Radhika Krishnan, Chief Product Officer at Hitachi Vantara, and Eric Hirschhorn, Chief Data Officer at BNY Mellon. Together, they will discuss:

- Why using DataOps will alleviate pressure on IT resources
- How DataOps can unlock value from existing data
- Why employee buy-in is so crucial
- The importance of leadership in creating a DataOps strategy

Harvard Business Review: Aligning Business Goals with Data Strategy

Join this TDWI Coffee Talk Webinar with David Stodder, Senior Director of Research for BI, TDWI and Charles Chatt, Director, Lumada Software Presales Solution Engineering, to learn strategies for addressing pain points in data pipeline development, deployment, and management. In particular, we will discuss DataOps as a framework for efficient growth and higher satisfaction in meeting data-driven business demands for the right data at the right time.
Topics include:
• How DataOps and CI/CD practices help organizations tackle data pipeline growth and complexity
• Treating data pipelines as a product: Changing mindsets about measuring the value of data pipeline
• Data observability and monitoring for troubleshooting problems and ensuring success
• The role of data intelligence for faster data pipeline development, improved quality, and data governance
• Aligning different types of data pipelines, including ETL, ELT, and real-time data streaming, with the variety of use cases

Modernizing Data Pipelines

Data Management

Data modernization

Data Analytics

data pipeline

Data Fabric

data catalog

Modernization

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Modernizing Data Pipelines

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