How Fivetran Automates Data Movement for Global Enterprises

Don't Panic! It's Just Data

#Business #Tech #MBA #EM360Tech #Safe Software

30:23

Tiffany Yu is the CEO & Founder of Diversability, an award-winning social enterprise to elevate disability pride; the Founder of the Awesome Foundation Disability Chapter, a monthly micro-grant that has awarded $92.5k to 93 disability projects in 11 countries; and the author of The Anti-Ableist Manifesto: Smashing Stereotypes, Forging Change, and Building a Disability-Inclusive World. As a person with visible and invisible disabilities stemming from a car crash, Tiffany has built a career on disability solidarity. Now that she has found success, she works to expand a network of people with disabilities and their allies to decrease stigmas around disability and create opportunities for disabled people in America. Episode Chapters 0:00 Intro 1:26 When do we choose to share our disability stories? 4:12 Jay’s disability story 8:35 Visible and invisible disabilities 13:10 What does an ally to the disability community look like? 16:34 NoBodyIsDisposable and 14(c) 21:26 How does Tiffany’s investment banking background shape her advocacy? 27:47 Goodbye and outro For video episodes, watch on www.youtube.com/@therudermanfamilyfoundation Stay in touch: X: @JayRuderman | @RudermanFdn LinkedIn: Jay Ruderman | Ruderman Family Foundation Instagram: All About Change Podcast | Ruderman Family Foundation To learn more about the podcast, visit https://allaboutchangepodcast.com/…

about a year ago 13:40

MP3•Episode home

In this episode, Rachel Thornton, Fivetran's CMO, discusses the highlights of Big Data London 2024, including the launch of Fivetran Hybrid Deployment, which addresses the needs of organisations with mixed IT environments.

The conversation delves into integrating AI into business operations, emphasizing the importance of a robust data foundation. Additionally, data security and compliance challenges in the context of GDPR and other regulations are explored. The episode concludes with insights on the benefits of hybrid deployment for organisations.

Key Takeaways:

Big Data London 2024 is a significant event for data leaders.
Fivetran Hybrid Deployment caters to organizations with mixed IT environments.
AI integration requires a strong data foundation.
Data security and compliance are critical in today's landscape.
Organizations must understand their data sources for effective AI use.
Hybrid deployment allows for secure data management.
Compliance regulations are becoming increasingly stringent.
Data readiness is essential for AI integration.

Chapters:

00:00 - Introduction to Big Data London 2024

02:46 - Launch of Fibntran Hybrid Deployment

06:06 - Integrating AI into Business Operations

08:54 - Data Security and Compliance Challenges

11:50 - Benefits of Hybrid Deployment

144 episodes

How Fivetran Automates Data Movement for Global Enterprises

Don't Panic! It's Just Data

13 subscribers

published about a year ago

MP3•Episode home

Key Takeaways:

Big Data London 2024 is a significant event for data leaders.
Fivetran Hybrid Deployment caters to organizations with mixed IT environments.
AI integration requires a strong data foundation.
Data security and compliance are critical in today's landscape.
Organizations must understand their data sources for effective AI use.
Hybrid deployment allows for secure data management.
Compliance regulations are becoming increasingly stringent.
Data readiness is essential for AI integration.

Chapters:

00:00 - Introduction to Big Data London 2024

02:46 - Launch of Fibntran Hybrid Deployment

06:06 - Integrating AI into Business Operations

08:54 - Data Security and Compliance Challenges

11:50 - Benefits of Hybrid Deployment

144 episodes

#Business #Tech #MBA #EM360Tech #Safe Software

All episodes

Don't Panic! It's Just Data

1
AI’s Silent Killer: Technical Debt & the Hidden Costs of Bad Data 23:20

6 days ago23:20

23:20

Enterprises face one common problem: the hidden costs of AI-based technical debt. “There’s a lot of hype around AI, but many initiatives aren't founded in a business value proposition,” says Paul Brownell, CTO, Growth Acceleration Partners (GAP). “People wander in without an intentional path for ROI.” In this episode of the Don't Panic, It's Just Data podcast , host Douglas Laney , BARC Research and Advisory Fellow, and author of Infonomics and Data Juice, speaks with Paul Brownell from GAP and Frank Lavigne, Advisory Board Member of CloudArmy. The speakers ultimately agree that AI promises greater returns on investment (ROI). However, it’s imperative to note – without a strong data foundation and strategy, AI can quickly turn into a financial nightmare. AI’s Potential to Cause Technical Debt Alluding to a significant “leak in the bucket” for AI initiatives, Brownell says, "a lot of these projects aren't founded in a business value proposition." This can often lead to organisations "wandering in without an intentional path." Both Brownell and Lavigne agreed that the most overlooked and costly area is data engineering . Lavigne exemplified this by referring to a meme depicting a sleek F-35 jet labelled "your AI" flying above a pockmarked, potholed road labelled "your data infrastructure." "I think that pretty much says it all," Lavigne stated, highlighting the critical and often unglamorous role of data engineering. Brownell resonated with this, calling it "mundane, routine, detail, hard pick and shovel work." Without mighty data quality , data governance , and traceability, AI projects are built on unsteady ground. Such AI initiatives occasionally result in inaccuracies and create a lack of trust. Scientific Path to AI Initiatives in Data Brownell advocated for a scientific approach to AI initiatives to overcome the hidden costs and maximise ROI. He said, "Come up with a hypothesis around where the business value is going to be, then apply some prototyping. Do real-life experiments to prove out your theory." Such an approach allows organisations to adjust course quickly. "The larger the ship, the harder it is to turn. So if you have these smaller kinds of proofs of concept, you can kind of find out in smaller increments how far we're off course,” explained Lavigne. This lowers risk and paves the way for more experimentation. Takeaways AI investments can create hidden financial burdens. Data readiness is crucial for successful AI initiatives. A hypothesis-driven approach can guide AI projects. Iterative experimentation leads to better outcomes. Data engineering is essential but often overlooked. Generative AI can assist in data pipeline management. Selecting AI tools requires flexibility and speed. Purpose-built AI models may outperform generative models. Organisations must foster a culture of continuous learning. Understanding the total cost of ownership for AI is vital. Chapters 00:00 Uncovering AI Technical Debt 04:56 Data Readiness for AI Initiatives 09:55 Selecting the Right AI Tools 13:06 Generative AI vs Predictive AI 18:14 The Future of AI Development About GAP Growth Acceleration Partners is a consulting and technology services company that provides custom software, data engineering and modernisation solutions. GAP works to consult, design, build, and modernise revenue-generating software and data engineering solutions for clients. Their remote, integrated engineering teams help businesses achieve a competitive advantage through technology. Using AI, proprietary tools and seasoned experience, GAP’s end-to-end approach spans from consultation and migration services to full-cycle digital product development and managed services, ensuring the solutions delivered are innovative and align with your business goals. GAP transforms the way companies do business, helping clients to stay ahead of technology trends in a rapidly evolving digital landscape. Working with GAP, you are able to achieve operational efficiency and revenue goals with custom software that drives results.…

Don't Panic! It's Just Data

1
The Infinity Loop: What's Trapping Financial Institutions in Data Patching? 33:33

16 days ago33:33

33:33

Organisations often find themselves trapped in an infinite loop. Typically hailed as an "infinity loop" or "patching loop,” it’s differentiated by a continuous cycle of fixing problems, patching, and redoing data pipelines just to maintain operations. “It's a trap that many financial institutions, banks, insurance companies, and more fall into. This loop or this cycle is a process of focusing on fixing problems, patching,” describes Errol Rodericks. In this episode of the Don't Panic It's Just Data podcast , Errol Rodericks, Product & Solutions Marketing and Sales Enablement Specialist at Denodo, discusses the challenges faced by financial services in steering the infinity loop of reactive data management. He emphasises the importance of breaking free from this cycle to achieve real innovation and success in AI-led initiatives. The conversation explores the significance of AI-ready data, the journey from bronze to gold data products, and how Denodo helps bridge the last-mile gap in data management . The Cost of Poor Data "The cost of poor data isn't just bad decisions. It's the decisions you never knew you could make. You never get around to that." This statement sets the stage for the podcast. It captures the profound effect of being stuck in a reactive data mode and how organisations can overcome it. Rodericks believes that financial services are entirely missing out on strategic opportunities that could redefine their market position. While many financial institutions have invested heavily in centralised lakehouse architectures like Snowflake or Databricks. These alone are not enough. They often struggle to deliver the trusted, real-time insights that Gen AI and business teams require. Missed Opportunities to Measurable Outcomes It becomes more challenging for financial institutions to deliver adequate Gen AI real-time data insights when dealing with the "missing mile" of data. Approximately 30 per cent of crucial data is often overlooked or inaccessible. To overcome the Gen AI challenges, Denodo facilitates logical data management. The firm provides direct access to live, relevant, and governed data when it's needed. It becomes critical for achieving measurable outcomes with AI-led initiatives. For Chief Financial Officers (CFOs), Rodericks offered a succinct but powerful message – "Modern finance isn't about reports... It's about your ability to predict, to personalise, and to prevent – the three Ps." Takeaways The infinity loop is a trap for financial institutions. Reactive data handling leads to missed insights and customer churn. Breaking out of the infinity loop is essential for innovation. AI projects often fail due to unreliable data inputs. AI-ready data must be trusted, timely, contextual, and reusable. The journey from bronze to gold data products is strategic. Ownership of data products is crucial for success. Timeliness of data is critical in financial services. Denodo provides real-time access to data without copying it. Modern finance focuses on prediction, personalisation, and prevention. Chapters 00:00 Understanding the Infinity Loop in Financial Services 04:23 Breaking Free from the Infinity Loop 06:03 The Cost of Firefighting Mode 09:14 The Importance of AI-Ready Data 19:42 The Journey from Bronze to Gold Data Products 22:53 Bridging the Last Mile Gap 27:06 Real-World Examples of Data Product Success 32:20 Key Takeaways for CFOs…

Don't Panic! It's Just Data

1
Don't Just Forecast, Flourish: The Integrated Path to Financial Agility 24:43

27 days ago24:43

24:43

Blending financial planning directly into existing business intelligence (BI) platforms like Microsoft Power BI and Qlik are on the rise. But have you questioned why, and what drives this shift? In this episode of the Don’t Panic It’s Just Data podcast , Kevin Petrie, BARC analyst, sits down to chat with Thomas Gorr, Director of Product Management for xP&A and BI at insightsoftware, and Henri Rufin, Head of Responsible Data & Analytics at Radiall. The speakers stress how the integration of financial planning in BI platforms is driven by the need to move beyond traditional Excel-based planning. This is because it often leads to data silos and errors. Their conversation spotlights how integrated BI and planning solutions improve collaboration across departments. Going deeper, BI can also provide a unified view of data and help organizations be more agile and proactive in volatile markets. Gorr and Rufin explain how separating your financial data makes less sense, and why traditional tools like Excel are no longer significant. Watch this podcast to discover how embedding planning capabilities within BI platforms, such as Qlik and Power BI , offer a seamless experience, greater flexibility, and real-time collaboration. Learn how organisations are adapting to volatile market conditions through agile planning, and gain a glimpse into the evolving landscape of financial planning. Tune in to gain expert insights and practical strategies for a more collaborative and data-driven future! Takeaways The integration of planning into BI platforms is essential for collaboration. Excel is prone to errors and creates silos in data management. Organizations need to adapt to dynamic market conditions for effective planning. Stakeholder engagement is crucial for successful financial planning. Advanced planning solutions offer flexibility and real-time collaboration. Data governance is necessary to support planning processes. The total cost of ownership is lower with integrated planning solutions. BI platforms provide a unified experience for users. Future planning will focus on platform integration and advanced analytics. Companies must evolve their planning capabilities to remain competitive. Chapters 00:00 Introduction to Financial Data Management 03:04 The Shift Towards Integrated Planning 08:30 Collaboration in Dynamic Markets 11:05 The Role of Stakeholders in Planning 15:10 Moving Beyond Excel 19:19 Total Cost of Ownership in Planning Solutions 25:06 Future of Integrated Financial Planning About insightsoftware insightsoftware is a global provider of comprehensive solutions for the Office of the CFO. They believe actionable business strategies begin and end with financial data that’s accessible and easy to understand. They offer solutions across financial planning and analysis (FP&A), accounting, and operations. This transforms how teams operate, empowering leaders to make timely and informed decisions.…

Don't Panic! It's Just Data

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Your Data’s GPS: Navigating Modernisation with Precision 26:52

5 weeks ago26:52

26:52

In this episode of the Don’t Panic, It’s Just Data podcast , Kevin Petrie, VP of Research at BARC, is joined by Nidhi Ram, Vice President of Global Services Strategy and Operational Excellence at Precisely. The duo explore the idea of focusing on data modernisation and improving accessibility rather than constantly implementing new technologies. Both Petrie and Ram highlight the importance of traditional mainframes, especially in modern data strategies. They delve into how companies can combine cloud tools with data in order to handle diverse data systems. This removes the need for replacing the mainframe, keeping the data accessible for all users. Going into the critical role of data quality and governance — especially in the age of AI — Ram emphasises that “garbage in, garbage out” has never been more relevant, as AI outputs are only as good as the data feeding the model. What's needed is a more comprehensive approach to data integration, quality, governance, and enrichment that helps ensure data is always ready for confident business decisions. Listen to this latest episode to learn how Precisely’s Data Integrity Suite provides a comprehensive approach to data modernisation. Takeaways Data modernisation is about accessibility, not technology. The mainframe continues to play a crucial role in data strategies. High-quality data is essential for successful AI initiatives. Data governance is critical to comply with regulations and ensure data quality. Cloud solutions offer flexibility, but on-premise systems provide control. Companies need to adapt to a heterogeneous data environment. Integrating people and processes is key to successful data programs. Future data roles will require broad functional knowledge rather than deep technical skills. Chapters 00:00 Introduction to Data Modernization 02:56 Understanding Data Modernization 06:01 Challenges in Data Modernization 08:53 The Role of AI in Data Strategies 11:56 Data Quality and Governance 15:08 Cloud vs On-Premise Data Solutions 18:14 Adapting to Diverse Data Environments 20:47 Advice for Modernizing Data Strategies 23:58 The Importance of People and Process 27:07 Future Skills for Data Teams About Precisely Precisely is a leading global data integrity provider, ensuring organisations have accurate, consistent, and contextual data. In today's data-driven world, where businesses rely on information for critical decisions, data integrity is crucial. Precisely offers a comprehensive portfolio of solutions designed to transform raw data into a reliable asset. Trusted by over 12,000 organisations in more than 100 countries, Precisely plays a critical role in helping businesses effectively leverage their data. By providing reliable software and strategic services, Precisely empowers organisations to confidently embark on their AI, automation, and analytics initiatives. High-quality, trustworthy data is the bedrock for successful AI models, efficient automation processes, and insightful analytics. Without it, these initiatives risk delivering inaccurate results and misleading insights. Precisely's commitment to data integrity allows businesses to make confident decisions and achieve strategic objectives.…

Don't Panic! It's Just Data

1
Leading Up to The Peak: Can Data Integration Solve Key Enterprise Challenges? 10:24

10 weeks ago10:24

10:24

In this episode of the Don't Panic, It's Just Data podcast, hosted by EM360Tech's podcast producer, Shubhangi Dua speaks to Donnie Owsley from Snohomish County, and Jeff Burton and Tom Lavery from the University of British Columbia. All of the speakers will be presenting at the upcoming Peak of Data and AI event, organised by Safe Software , the creators of FME. Scheduled to take place in Seattle from May 5th to 8th, 2025, The Peak is an exciting gathering for data and AI innovators. This conversation offers a preview of some of the practical applications and insights that will be shared at the event. The podcast also talks about the development of creative solutions for enhancing accessibility in urban environments. The UBC speakers particularly refer to their creation of an accessible university campus navigation system, a project that showcases the power of integrating FME with platforms like ArcGIS. This discussion spotlights the challenges and ingenuity involved in building inclusive wayfinding solutions that cater to the diverse needs of a community. The conversation sheds light on some tangible ways in which FME is being used across different sectors to tackle specific challenges and boost creative innovations. It provides valuable context for the types of practical knowledge and problem-solving approaches that will be central to The Peak of Data and AI event. For further information on what we’ve talked about and to register for The Peak of Data and AI event in Seattle, please head over to peakofdataintegration.com . Key Highlights Discover how to use tools like FME for preemptive IT issue resolution. Learn the approach to creating inclusive navigation systems with FME and ArcGIS. Get practical insights into current industry applications. Preview actionable data and AI solutions. Explore the versatile application of FME in your organisation. About Safe Software Founded in 1993, Safe is headquartered in Surrey, BC with over 200 team members and counting. We’re always looking for talented individuals with diverse backgrounds who are determined to learn and grow. Over 20,000 organisations around the world use FME in industries like AEC, government, utilities, and transportation to maximise the value of their data.…

Don't Panic! It's Just Data

1
Is Your Finance Team Stuck in the Past? Real-Time Answers 27:14

11 weeks ago27:14

27:14

Takeaways #Financeteams are often resistant to change, clinging to outdated tools. Real-time data integration can help break down data silos and better decision-making. The shift from FP&A to XP&A emphasises collaboration across departments. #Datagovernance is crucial when handling financial data. Real-time data enables more accurate forecasting and budgeting. Organisations should define their data strategy before implementation. Proactive adaptation to data technologies is essential for future success. Summary In this episode of " Don't Panic, It's Just Data ," host Christina Stathopoulos explores the world of real-time analytics and its impact on financial decision-making. She is joined by Thomas Gore, insightsoftware's Director of Product Management for extended planning and analysis (XP&A), and Cody Riemenschneider, Director of Solutions Engineering, and they discuss the challenges and opportunities of integrating real-time data into finance. We explore the issue of data silos and how real-time AI integration can break them down. Thomas explains: "Each department has its own data report, its own planning tools, which are mostly Excel files... They don't collaborate." Listen to our latest podcast now for an insightful conversation on how real-time data is reshaping the future of #financialplanning and analysis. For the latest tech insights visit: EM360Tech.com…

Don't Panic! It's Just Data

1
Building Trust in Data: Transparency, Collaboration, and Governance for Successful AI 22:59

12 weeks ago22:59

22:59

"So you want trusted data, but you want it now? Building this trust really starts with transparency and collaboration. It's not just technology. It's about creating a single governed view of data that is consistent no matter who accesses it, " says Errol Rodericks, Director of Product Marketing at Denodo . In this episode of the 'Don't Panic, It's Just Data' podcast, Shawn Rogers, CEO at BARC US, speaks with Errol Rodericks from Denodo . They explore the crucial link between trusted data and successful AI initiatives. They discuss key factors such as data orchestration, governance , and cost management within complex cloud environments. We've all heard the horror stories – AI projects that fail spectacularly, delivering biased or inaccurate results. But what's the root cause of these failures? More often than not, it's a lack of focus on the data itself. Rodericks emphasises that "AI is only as good as the data it's trained on." This episode explores how organisations can avoid the "garbage in, garbage out" scenario by prioritising data quality, lineage, and responsible AI practices. Learn how to avoid AI failures and discover strategies for building an AI-ready data foundation that ensures trusted, reliable outcomes. Key topics include overcoming data bias, ETL processes, and improving data sharing practices. Takeaways Bad data leads to bad AI outputs. Trust in data is essential for effective AI. Organisations must prioritise data quality and orchestration. Transparency and collaboration are key to building trust in data. Compliance is a responsibility for the entire organisation, not just IT. Agility in accessing data is crucial for AI success. Chapters 00:00 The Importance of Data Quality in AI 02:57 Building Trust in Data Ecosystems 06:11 Navigating Complex Data Landscapes 09:11 Top-Down Pressure for AI Strategy 11:49 Responsible AI and Data Governance 15:08 Challenges in Personalisation and Compliance 17:47 The Role of Speed in Data Utilisation 20:47 Advice for CFOs on AI Investments About Denodo Denodo is a leader in data management. The award-winning Denodo Platform is the leading logical data management platform for transforming data into trustworthy insights and outcomes for all data-related initiatives across the enterprise, including AI and self-service. Denodo's customers in all industries all over the world have delivered trusted AI-ready and business-ready data in a third of the time and with 10x better performance than with lakehouses and other mainstream data platforms alone.…

Don't Panic! It's Just Data

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Why is a Customer Data Strategy a Competitive Edge? 30:18

13 weeks ago30:18

30:18

Takeaways #CMDM is essential for creating a unified and accurate view of the customer. Trust comes from how responsibly data is handled. Ethical data use is a competitive advantage and builds trust. Executive sponsorship and cross team buy-in is crucial for MDM projects. A strong customer #datastrategy is a competitive edge, not a side project. Summary Customer Master Data Management (CMDM) as Matthew Cawsey, Director of Product Marketing at Stibo Systems describes, "about having a master record of a customer, as opposed to many organisations where customer data gets created and authored in potentially dozens of different CRMs, ERPs, and finance systems.” In this episode of our ' Don't Panic, It's Just Data' podcast series, Christina Stathopoulos, Founder at Dare to Data, speaks with Matthew Cawsey and Arnjah Dillard from Stibo Systems. Matthew and Arnjah explain the importance of CMDM and CXDC for maintaining positive customer engagement. Learn how to move from basic personalisation, ethically use #data, leverage #AI for a better customer experience. Let’s transform your messy data into a competitive advantage. For the latest tech insights visit: EM360Tech.com…

Don't Panic! It's Just Data

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The Peak of Data and AI: Speaker Sneak Peek 8:40

13 weeks ago8:40

8:40

In the latest episode of the Don’t Panic It’s Just Data podcast, we connected with speakers who provided a preview of their presentations at the upcoming Peak of Data and AI event in Seattle organised by Safe Software from May 5-8, 2025. This premier gathering, hosted by Safe Software , the creators of FME , will be a hub for data and AI innovators, and this podcast episode offers an exclusive look into what attendees can expect. Our conversation featured Margaret Smith and Reshma Joy from the West Virginia Department of Transportation. They shared their crucial work in ensuring data integrity through rigorous validations of their Linear Reference System data. This foundational work underpins much of their operational efficiency and decision-making. They further revealed how they’ve achieved seamless integration between Survey123 and their R&H data, showcasing a strong example of how disparate systems can be harmonized for greater insight. This presentation will provide attendees with actionable strategies for enhancing data quality and interoperability. We also spoke to Bruno Blanco, a GIS Engineer from Shelby County 9-1-1. Bruno walked us through how FME supports critical aspects of their 911 addressing workflow—particularly data aggregation , QA/QC, and attribution—within a larger automation framework. This work highlighted the power of automation in critical public safety infrastructure. By streamlining their addressing processes, Shelby County 9-1-1 is improving response times and ensuring more accurate location data, ultimately saving lives. Bruno’s presentation will offer valuable insights into how organisations can leverage FME to automate complex workflows and enhance operational efficiency. This episode serves as a compelling preview for the main event at The Peak of Data and AI. If you’d like to learn more about Bruno and Shelby County 9-1-1’s story, check out their success story with Safe. For further information on what we’ve talked about and to register for The Peak of Data and AI event in Seattle, please head over to peakofdataintegration.com. Takeaways Data validation is essential for accurate operations. FME enables seamless integration of disparate systems. Automation of critical processes improves public safety. Networking and community learning are key benefits of The Peak. Breakout sessions provide valuable hands-on FME knowledge. AI is increasingly influencing data integration workflows.…

Don't Panic! It's Just Data

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Mastering Collaborative Financial Planning 31:46

15 weeks ago31:46

31:46

"There's been a lot of wrangling of data, a lot of wrangling of humans as well, which is a big theme for today," says Warwick Leitch, Product Management Director at insightsoftware. In this episode of the ' Don't Panic, It's Just Data ' podcast, Debbie Reynolds, CEO and Chief Data Privacy Officer at Debbie Reynolds Consulting LLC, speaks with Leitch from insightsoftware. They discuss the vital role of financial strategy and collaborative planning, particularly as it pertains to the decisions made by IT executives. The question they address is: In a world awash with data, how do we transform it into actionable insights? Warwick shares his wealth of experience, offering practical advice and illuminating the path to successful budgeting and forecasting. One such challenge addressed in the podcast is how organisations are securing executive buy-in. "And 51 percent of people find it difficult to engage senior executives to buy into the process, which is a roadblock. And 57 percent of organisations struggle cross-functionally," Warwick reveals. It's not just about the numbers. Warwick also emphasises the human element, reminding us that "Without people, we don't have anything." In an era where AI looms large, it's crucial to remember that technology serves to enhance, not replace, human collaboration. Tune in to the podcast and learn how to navigate the complexities of financial strategy and collaborative planning. Takeaways Executive buy-in is crucial for successful budgeting. A clear vision helps guide the budgeting process. Thoughtful execution is key to effective planning. Fostering a culture of collaboration enhances participation. Data accuracy is vital in today's fast-paced environment. Avoid overcomplicating the budgeting process. Gamification can improve engagement in budgeting. AI can significantly streamline forecasting and reporting. Regularly updating forecasts leads to better accuracy. Understanding business measures is essential for effective planning. Chapters 00:00 Introduction to Collaborative Financial Planning 05:01 The Importance of Executive Buy-In 10:09 Thoughtful Execution in Budgeting 15:01 Fostering a Culture of Collaboration 19:48 Defining Business Measures and Data Accuracy 24:52 Common Pitfalls in Collaborative Budgeting 29:52 The Future of Collaborative Planning with AI…

Don't Panic! It's Just Data

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The Future of Data Centres Energy 35:31

18 weeks ago35:31

35:31

The digital age is fueled by data, and the engines powering that data are data centres. However, this growth comes at a significant energy cost. In the latest episode of the EM360Tech Don’t Panic It’s Just Data podcast, Shubhangi Dua speaks with Rolf Bienert, Technical & Managing Director of the OpenADR Alliance , to shed light on the urgent need for sustainable energy practices within the data centres industry. In this episode, we discuss the stark reality of escalating energy consumption, driven by factors like the rise of AI, and the critical importance of moving beyond superficial "green" initiatives to implement genuine, impactful solutions. From talking about the historical context of data centres energy usage, the evolution of energy demands and the challenges of achieving net-zero goals, Rolf provides valuable insights into innovative solutions such as smart grids, microgrids, and virtual power plants. These hold immense potential for managing energy distribution efficiently and sustainably. Beyond technological solutions, the podcast addresses the critical role of regulatory frameworks and industry standards in fostering sustainable practices. The frameworks are necessary to adapt to modern energy consumption patterns, ensuring interoperability and reducing costs. It spotlights the importance of collaboration between IT and utility sectors, as well as open communication with the public, to address concerns about energy consumption and build trust. Takeaways Data centres are increasingly becoming significant consumers of energy. Sustainability in data centre is often perceived as branding rather than genuine effort. AI's demand for processing power is escalating energy needs. Smart grids are essential for managing energy distribution effectively. Microgrids and virtual power plants offer promising solutions for energy sustainability. Enterprises can leverage renewable energy to become energy providers. Regulatory frameworks need to adapt to modern energy consumption patterns. Standards are crucial for ensuring interoperability and reducing costs. Collaboration between IT and utility sectors is vital for sustainable energy management. Open communication is key to addressing public concerns about energy consumption. Chapters 00:00 Introduction to Data Centres Sustainability 03:22 Historical Perspective on Data centres Energy Consumption 08:32 The Role of Smart Grids in Energy Management 12:40 Understanding Microgrids and Virtual Power Plants 21:30 Enterprise Strategies for Sustainable Data Centres 29:51 Regulatory Challenges and Opportunities 32:34 The Importance of Standards in Data Centres Growth…

Don't Panic! It's Just Data

1
Data Trust or Bust: The Key to AI Success 18:27

21 weeks ago18:27

18:27

As organisations strive to stay competitive in the age of AI, data trust has become a critical factor for success. Without it, even the most advanced AI initiatives are bound to fall short. With the rapid advancement of technology, prioritising trust in data is essential for unlocking AI's full potential and driving meaningful results. Conversely, a lack of data trust can undermine decision-making, operational efficiency, and the success of AI initiatives. In this episode, Christina Stathopoulos, Founder at Dare to Data, speaks to Jay Limburn, Chief Product Officer at Ataccama, to explore these pressing topics. Together, they share actionable insights, real-world examples, and innovative strategies to help businesses harness the power of trusted data. Key Takeaways Data trust is essential for confident decision-making. AI can significantly reduce mundane tasks. Organizations must focus on their data strategy. Customer experience is a key area for AI application. Data teams are crucial for successful AI initiatives. Proactive data management is becoming the norm. The chief data officer's influence is growing. Data quality and security are critical challenges. AI can enhance regulatory reporting processes. Trust in data is vital for successful AI projects. Chapters 00:00 - Introduction to Data Trust and AI Integration 09:36 - The Role of AI in Operational Efficiency 12:47 - Balancing Short-term and Long-term Data Priorities 15:00 - Enhancing Customer Experience through AI 19:08 - Aligning Workforce and Culture for AI Success 21:03 - Innovative Strategies for Data Quality and Security 24:35 - Final Thoughts on Data Trust and AI Success…

Don't Panic! It's Just Data

1
Mapping Success: How FME Powers the San Antonio River Authority’s Data Journey 19:52

22 weeks ago19:52

19:52

The San Antonio River Authority (SARA) has experienced a transformative shift in data management, thanks to the powerful capabilities of FME. By integrating FME, SARA has streamlined data integration, improved efficiency, and enhanced decision-making processes across multiple departments. FME’s ability to automate data transformation, standardise formats, and manage large volumes of spatial data has allowed the authority to optimise workflows, reduce manual errors, and accelerate project timelines. A key highlight of SARA’s success with FME is its use in predictive flood modelling and the standardisation of data workflows. By leveraging FME, SARA can more accurately predict flood risks, improving public safety and response times. This innovation not only enhances internal operations but also helps SARA lead in sustainable water management. With its versatility in handling diverse data sources and streamlining communication between systems, FME is a powerful investment for organisations seeking to improve operational efficiency and long-term strategic decision-making. In this episode, Debbie Reynolds, Founder and Chief Data Privacy Officer at Debbie Reynolds Consulting, speaks to Jordan Merson, Enterprise Applications Supervisor at San Antonio River Authority, about the game-changing impact of FME. Key Takeaways: Data management challenges often stem from a lack of standardisation. FME allows for the integration of various data sources seamlessly. Predictive modelling can enhance emergency response efforts. FME provides tools for real-time data monitoring and alerts. The user-friendly interface of FME accelerates onboarding for new team members. FME can handle both spatial and non-spatial data effectively. Collaboration and knowledge sharing are key to successful data management. Chapters: 00:00 - Introduction to Data Management and FME 02:30 - Jordan's Journey in IT and Data Management 05:43 - Challenges Before FME Implementation 08:36 - Transformative Impact of FME on Data Processes 10:02 - Real-World Applications of FME at San Antonio River Authority 14:06 - Predictive Flood Modeling and Emergency Operations 16:31 - Standardization and Efficiency with FME 17:59 - Final Thoughts and Recommendations on FME…

Don't Panic! It's Just Data

1
Navigating the Edge: Data Management Strategies 20:56

23 weeks ago20:56

20:56

Summary This discussion explores the complexities and strategies surrounding edge computing and data management, highlighting the importance of security, the challenges of vendor lock-in, the implications of data repatriation, and the necessity of ensuring high-quality data for AI systems. It emphasises the need for organisations to balance edge processing with centralised storage while future-proofing their data strategies against rapid technological changes. Building on their discussion, Jimmy Tam highlights the transformative role of edge computing in modern data management, emphasising the importance of governance, compliance, and interoperability to address the challenges of data sprawl and vendor lock-in. Takeaways Edge computing is transforming how organisations manage data. Security at the edge is paramount to prevent intrusions. Data sprawl poses significant challenges for edge data management. Governance and compliance are essential for effective data management. Vendor lock-in can limit flexibility and adaptability in technology. Data interoperability is crucial for avoiding vendor lock-in. Data repatriation is a growing trend among organisations. AI systems require access to comprehensive data for training. Speed of data relevance is critical for effective AI applications. Flexibility in data strategies is essential for future-proofing organisations. Sound Bites "Data sprawl is a significant problem." "Governance and compliance are crucial." "Data repatriation is absolutely real." "Speed of data relevance is critical." Chapters 00:00 Introduction to Edge Computing and Data Management 02:53 Security Strategies for Edge Data 06:06 Vendor Lock-In and Data Interoperability 09:00 Data Repatriation and Cost Optimisation 11:57 Ensuring Quality Data for AI Systems 14:46 Balancing Edge Processing and Centralised Storage 17:59 Future-Proofing Data Strategies…

Don't Panic! It's Just Data

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Rethinking Real-Time Analytics: Building the Foundation for Real-Time AI 22:54

26 weeks ago22:54