Data strategy guidelines for AI: A practical guide for IT leaders.
By: Informatica View more from Informatica >>
Download this next:
Prepare your data architecture for the demands of generative AI
By: Informatica
Type: Infographic
This infographic highlights challenges in preparing data architectures for generative AI. Key concerns include:
• Quality of Data (42%): Ensuring accuracy and reliability
• Data Privacy and Protection (40%): Safeguarding sensitive information
• AI Ethics (38%): Addressing ethical considerations
• Domain-specific Training Data (38%): Obtaining specialized data for fine-tuning models
• AI Governance (38%): Establishing responsible AI frameworks
These percentages likely show the proportion of organizations identifying each factor as a challenge. Modernizing data architectures requires attention to these elements for AI-ready environments.
Review the infographic for insights into GenAI success.
These are also closely related to: "Data strategy guidelines for AI: A practical guide for IT leaders."
-
Top IT predictions in APAC: 2021
By: TechTarget ComputerWeekly.com
Type: eGuide
Going by the predictions fleshed out by technology suppliers and analysts, the Asia-Pacific region will continue to be a cradle for technology innovation, whether it is 5G services, artificial intelligence (AI), cloud computing or cyber security.
In this infographic, we review some of the key IT trends that are likely to shape the industry in 2021.
-
Infographic: AI vs Predictive analytics
By: TechTarget ComputerWeekly.com
Type: Infographic
Predictive analytics and artificial intelligence (AI) help companies make better decisions by anticipating what will happen. Both approaches can predict future outcomes by analyzing current and past data. In this infographic, we take a look at their main characteristics and applications to understand how these tools are changing the decision-making process.
Find more content like what you just read:
-
Infographic: Mapping adoption of artificial intelligence in the enterprise
By: TechTarget ComputerWeekly.com
Type: eGuide
This infographic breaks down the complex data into noteworthy insights from enterprise leaders, including bottlenecks to AI development, budget allocation and what parts of their company see the most AI.
-
10 steps to harness the power of your data
By: forty8fifty
Type: White Paper
Ready to take your data analytics and AI strategies to the next level? In this white paper, you’ll discover a 10-step checklist for getting the most out of your data, analytics, and AI initiatives. Read on to discover how you can harness the power of your data and drive your organization’s competitive edge.
-
Operationalize Your AI Models: 4 key Elements
By: Red Hat
Type: White Paper
As organizations continue to adopt AI, the challenge quickly becomes operationalizing models effectively via a continuous machine learning operations (MLOps) process. How can you spin up this process in to ensure you deliver reliable AI results? Access this checklist now to learn 4 key methods of operationalizing AI successfully in the long-term.
-
The AI-Enabled Trusted Research Environment
By: Manifold
Type: White Paper
Trusted Research Environments are evolving to meet modern genomic research demands, including AI integration, secure collaboration, and scalable infrastructure. This white paper explores key features of TREs, from compliance and data management to AI-powered interfaces. Read the full white paper to learn how to leverage TREs for your research.
-
Generative AI: transforming drug discovery with purpose-built tools
By: AWS & NVIDIA
Type: Product Overview
Drug discovery is slow, expensive, and high-risk, taking over a decade and billions to bring a new drug to market. Generative and predictive AI are changing this by helping biopharma companies accelerate research, improve data analysis, and identify promising drug candidates faster. Download this solution brief to learn more.
-
Discover the power of multimodal AI for your business
By: Hewlett Packard Enterprise
Type: White Paper
Integrating diverse data streams like images, audio, and text can revolutionize business decision-making with multimodal AI. Learn how to boost your business IQ and drive efficiency by implementing this transformative technology. Read the full white paper to get started.
-
Manufacturing background checks 101: A checklist
By: Checkr
Type: White Paper
Streamline your manufacturing hiring process with AI-powered background checks. Learn how to create a seamless candidate experience, automate compliance workflows, and integrate with your HR tech stack. Read the full checklist to modernize your background screening.
-
10 signs that you're not AI-grade data-fit
By: Hitachi Pentaho
Type: eBook
Want to learn how to prepare your data for the demands of AI? In this e-book, you'll discover the 5 pillars of data-fitness and the risks of poor data quality in the age of AI. Download the e-book now to find out how you can build a data-first strategy for your AI initiatives.
-
Explore Predictive Analytics and AI-Driven Data Fitness
By: Hitachi Pentaho EMEA
Type: eBook
Want to learn how to prepare your data for the demands of AI? In this e-book, you'll discover the 5 pillars of data-fitness and the risks of poor data quality in the age of AI. Download the e-book now to find out how you can build a data-first strategy for your AI initiatives.
-
Advanced Analytics
By: OneStream Software LLC
Type: White Paper
Advanced analytics can help finance teams move beyond the monthly reporting cycle and leverage data for faster, more informed decision-making. Access this white paper to learn how OneStream's solutions can empower your finance organization to take advanced analytics further.
-
4 Steps to Transform your Company with Data & AI Powered by Data Cloud
By:
Type: Video
AI and Data have a symbiotic relationship; the intelligence of AI is only as good as the data it's fed. The quality and scale of good data is the one that empowers AI to identify relevant patterns, make predictions, and automate complex tasks. And while every organization is racing to deliver AI and it's benefits across their solutions, but how can you deliver trusted AI that understands your business and your customers? Watch this webinar and learn how to: - Unlock trapped data to build a foundation for trusted AI to scale your teams and grow your business - Harness the power of Data Cloud to build a unified 360-degree view of your customer every team can act on - Incorporate predictions to automate business actions in the flow of work
-
Gain visibility on change risk to eliminate production failures
By: Digital.ai
Type: Product Overview
Predict and mitigate change failure risks in your application environment. Learn how Digital.ai Intelligence - Change Risk Prediction can help you make data-driven decisions, accelerate agility, and reduce costs associated with production incidents. Read the full product brief.
-
MicroScope – December 2023: What does the future hold for Industry 5.0?
By: MicroScope
Type: Ezine
In this issue, we explore the future of Industry 5.0 to discover whether it's truly a tech revolution or just the next step in what has been promised since Industry 4.0. Also learn more about the risks and impacts of generative AI on data compliance and compliance, as well as seven steps you should take to engage customers while providing services
-
2025 Cybersecurity Predictions: Potential Risks of AI Adoption
By:
Type: Replay
Discover the potential risks of AI adoption in 2025. Our leaders will discuss the predicted impact of rapid AI adoption, regulation around AI and data privacy, and how cyber attackers are leveraging AI.
-
Explainable AI: Cutting Edge Developments for Dependable IoT Systems
By:
Type: Video
IoT technologies simplify remote access and continuous-time data sourcing from connected devices. Remote management and control capabilities, combined with AI/ML techniques, help organizations to improve industrial efficiency and operational predictability. However, the increasing use of black-box techniques for predictive diagnostics about the health of machines in factories or spare capacity in smart city transportation systems introduces a new element in decision making. How trustworthy is a predicted failure if it leads an engineer to shut down a production line? Or, how dependable are predictions about car parking spaces or shared bikes for commuters planning their city centre journeys? Explainable AI (XAI) is at the cutting edge of new techniques to increase confidence in predictions and to reason about diagnostics from AI and ML systems. XAI is also a key enabler to enforce digital rights under GDPR-like regulations. This panel will consider new developments in the field of AI, their implications for data life-cycle management and, the interplay between IoT and AI/ML disciplines when designing more dependable and trustworthy systems.
-
30 top edge computing companies to watch in 2022
By: TechTarget ComputerWeekly.com
Type: Infographic
With the amount of data organizations are generating today, IT leaders should consider edge computing technologies to keep all that data closer to the edge. In this infographic, we point out 30 vendors that are investing heavily in edge technologies to help organisations as they build edge computing ecosystems.
-
Digital.ai Intelligence – Change Risk Prediction
By: Digital.ai
Type: Podcast
Predict and mitigate change failure risks in your application environment. Learn how Digital.ai Intelligence - Change Risk Prediction can help you make data-driven decisions, accelerate agility, and reduce costs associated with production incidents. Read the full product brief.
-
Infographic: Gartner AI and compliance spending forecast
By: TechTarget ComputerWeekly.com
Type: eGuide
More than 60 jurisdictions around the world have proposed or are drafting postmodern privacy and data protection laws as a result. This infographic shows Gartner AI and compliance spending forecast.
-
Partners in Possibility | Episode 12: The Human Element in Prediction Technology
By:
Type: Video
We continue our conversation about AI and prediction technology with Avi Goldfarb, the Rotman Chair in AI and Healthcare at the University of Toronto, Chief Data Scientist at the Creative Destruction Lab, and co-author of the best-selling book “Prediction Machines” and its follow-up “Power and Prediction.” We look at how AI will change our industry, and the vital role human judgment plays in using this technology most effectively, and how we here at Plus Company are unlocking what’s possible in the consumer journey with our newest innovation, Plus AIOS.
-
Lights Out: AI in the Data Centre
By:
Type: Video
IN PARTNERSHIP WITH HUAWEI Latest examples of leveraging AI for efficient and resilient data centres How has the pandemic excelled the use case for AI The benefits of using predictive management of your assets When will data centres truly be ‘lights out’, if ever?
-
Embracing Next-Generation Automation: Four Thought Leaders on How AI Can Help Meet Evolving Marketing Challenges
By: Braze
Type: White Paper
This white paper explores AI's role in revolutionizing customer engagement, offering insights from experts on its impact, key use cases, and strategies. Learn how AI enhances personalization, automation, and marketing outcomes. Read the full white paper to discover leveraging AI for more effective customer experiences.
-
Unlock the Value of AI & Generative AI Quickly and at Scale with AWS & Teradata
By:
Type: Replay
Predictive insights are the lifeblood of today’s business. Imagine that your product team is coming up with new features, your operations team is investigating supply chain issues, and your marketing team is developing 360-degree profiles of customers. Wondering what these three scenarios all have in common? For a modern business operating in today’s dynamic environment, all three are powered by predictive analytics. Working behind the scenes, artificial intelligence (AI) and machine learning (ML) enable high- value predictions that lay the groundwork for better decision-making. These analytics, including the new promises of Generative AI, hold the power to sharpen your company’s competitive edge, drive operational efficiencies, and maximize growth. With Generative AI, your team of data scientists can streamline the way they make sense of ever-growing datasets. It allows them to automate tedious tasks like filtering and parsing huge volumes of data so they can draw out meaningful information. Join us to learn how leaders are hurtling the common pitfalls around AI workflows, how Teradata and Amazon Web Services (AWS) are penetrating barriers to predictive analytics, and how data scientists can scale analytics leveraging an integrated AI toolset.
-
Unleash AI Innovation Across the Enterprise with Teradata and AWS
By:
Type: Replay
Predictive insights are the lifeblood of today’s business. Imagine that your product team is coming up with new features, your operations team is investigating supply chain issues, and your marketing team is developing 360-degree profiles of customers. What do these scenarios have in common? For a modern business operating in today’s dynamic environment, all three are powered by predictive analytics. Increasingly, artificial intelligence and machine learning technology (AI/ML) is enabling high-value predictions that lay the groundwork for better decision-making. Advanced analytics, including generative AI, hold the power to sharpen your company’s competitive edge, drive operational efficiencies, and maximize growth. With generative AI, data scientists can more easily make sense of ever-growing datasets. They can automate tedious tasks like filtering and parsing huge volumes of data to quickly extract meaningful information. Join us to learn how leaders are overcoming the common pitfalls around AI workflows, how Teradata and Amazon Web Services (AWS) are penetrating barriers to predictive analytics, and how data scientists can scale analytics leveraging an integrated AI toolset.
-
10 predictions for the future of cloud
By:
Type: Video
In this webinar, experts from Google Cloud discuss how cloud is being shaped by data-driven systems and share predictions for its future such as why enterprises will invest heavily in AI-powered security, how AI will make systems use more and waste less at the same time, and where AI is poised to create more job opportunities. The webinar also shares how some organizations are turning these predictions into reality by minimizing costs, reducing onboarding time, and eliminating complexity.
-
Journey to Resiliency: How AI & ML Improve Predictive Maintenance & Optimization
By:
Type: Talk
For several years, artificial intelligence (AI) and machine learning (ML) have been trendy buzzwords in the data center industry, offering the promise of an automated data center that is more resilient with a lower operating cost. The reality is, most data center operators are still living in a reactive world; chasing down problems, issues, and putting out fires. We’re all hoping that predictive maintenance driven by AI/ML will change that, but this has become a longer journey than stakeholders first realized. The first step in this journey is to identify where your organization sits on the path of reactive, preventative, proactive, or predictive maintenance. The next step is to develop a plan for migrating towards predictive maintenance driven by AI/ML that will optimize your data center while improving resiliency. This session covers the key hurdles you’ll experience on this journey. We will present examples on how to achieve higher levels of optimization and resiliency by utilizing real-time monitoring that infuses predictive tools driven by AI/ML. We will also provide the game plan and C-level decision criteria you’ll need to obtain approvals and lead your organization though this journey.
-
AI Governance 101: AI and the mountains of unstructured data you hold
By:
Type: Video
If ever there was an underutilized resource in your organization, unstructured data would take first prize. Everything from emails, paper documents, pdf files, and sensor data from IoT devices all hold valuable data that generative AI LOVES. However, use of GenAI, like the predictive AI that came before it, requires the proper data and AI governance be leveraged including unstructured data classification, monitoring, and remediation.
-
AI Governance 101: AI and the mountains of unstructured data you hold
By:
Type: Replay
If ever there was an underutilized resource in your organization, unstructured data would take first prize. Everything from emails, paper documents, pdf files, and sensor data from IoT devices all hold valuable data that generative AI LOVES. However, use of GenAI, like the predictive AI that came before it, requires the proper data and AI governance be leveraged including unstructured data classification, monitoring, and remediation.
-
AI Governance 101: AI and the mountains of unstructured data you hold
By:
Type: Replay
If ever there was an underutilized resource in your organization, unstructured data would take first prize. Everything from emails, paper documents, pdf files, and sensor data from IoT devices all hold valuable data that generative AI LOVES. However, use of GenAI, like the predictive AI that came before it, requires the proper data and AI governance be leveraged including unstructured data classification, monitoring, and remediation.
-
Computer Weekly - 27 October 2020: Pet project: How Pets at Home cares for customers with data analytics
By: TechTarget ComputerWeekly.com
Type: Ezine
In this week's Computer Weekly, we talk to the chief data officer of Pets at Home, about using data analytics to care for customers. British Airways had its GDPR fine reduced to just £20m – we ask what this means for data protection regulation. And we look at GPT3, the language prediction tool that could revolutionise AI. Read the issue now.
-
Unveiling cybersecurity trends shaping the digital landscape in 2024
By: Cloudflare
Type: Analyst Report
This report explores key cybersecurity trends for 2024, including AI adoption, zero trust, data privacy, API security, and identity protection. It offers insights on regulatory compliance, tool consolidation, and budget priorities to help organizations tackle threats. Read the full white paper to prepare your security strategy for the future.
-
Predicting & Preventing Cybercrime in a Post COVID-19 World Using Big Data & AI
By:
Type: Talk
In a world that changed overnight to all digital because if the pandemic, a new wave of Cybercrime came with more vicious and a much larger scale. From simple email hacking to a large cyber terrorism crime, cyber criminals have had their best opportunity to take advantage of a world that became totally dependent on technology before it was ready for it. Yet, with all this gigantic amount of data collected from billions of people and the extreme speed of AI and Machine Learning advancements it might be easier to profile criminals, monitor their behaviors, predict their next move and stop it before it happened. How could this be achieved? This is the core focus topic of this session. Topics: - Cybercrime before and during COVID-19. - The growth of cybercrime during the pandemic and the effect on economy, business, education and healthcare. - Big Data and Mass Surveillance: How can AI and Big Data help profiling current and potential criminals. - AI Prediction Models for future cybercrime and how can it be utilized in predicting and stopping cybercrime before it happens. - Challenges of cybercrime prediction models: Bias, lack of info and accuracy level.
-
Predictive Insights From Battery Test Data
By:
Type: Video
Join us for a new webinar on Artificial Intelligence (AI) applied to battery testing. This session will showcase the potential for test engineers by demonstrating how to explore effectively, quickly, and easily build an AI-based solution with real battery test data to increase test plan efficiency. Through a live Monolith software demonstration, participants will gain practical insights into the following key aspects: - Loading and Exploring Battery Data: Learn the essential steps to load and explore battery data efficiently, laying the foundation for insightful analysis. - Model Training from Test Data: We'll give you step-by-step instructions on training AI models using your test data, empowering you to harness the predictive capabilities of AI. - Choosing the Right AI Algorithms: Explore diverse methods to evaluate AI models, enabling you to identify the best-fit models for your unique testing requirements. Understand how to determine the most suitable AI algorithms for your specific battery data, ensuring optimal model performance. - Predictive Battery Performance: Discover how AI models can be used to make accurate predictions of battery performance, enhancing the efficiency of testing processes. - Model Sharing for Collaborative Use: Learn strategies to share your AI models for broader collaboration, fostering a community-driven approach to battery testing innovation. - Optimising Test Plans with AI: Uncover the impact of AI models on optimising test plans, maximising efficiency, and ensuring comprehensive testing coverage.
-
AI in IT ops: High ROI and tangible business benefits
By: LogicMonitor
Type: Analyst Report
AI is transforming IT operations, driving a shift from reactive to proactive management. Learn how AI-driven tools are enhancing incident response, security, and ROI. Download the full report to explore the latest trends and strategic recommendations for maximizing the benefits of AI in IT operations.
-
SMBs in 2025: 10 predictions from analysts
By: T-Mobile for Business
Type: Research Content
In this IDC report, unlock 10 predictions about small and medium-sized businesses (SMBs) in 2025 and beyond.
-
Selecting an Enterprise Platform for Python and Open Source: A Checklist for Buyers
By: Anaconda
Type: Buyer's Guide
Thanks to its simplicity and versatility, Python remains the gold standard for data science work. The challenge remains: how to select the best Python platform to keep up with the newest techniques and best practices in data science. Access this buyer's guide to gain insights into this decision.
-
Explore how AI can enhance change and release management
By: Digital.ai
Type: White Paper
This whitepaper explores how AI and machine learning can enhance change and release management. Learn how predictive modeling, risk visualization, and incident prediction can make change management more agile and remove bottlenecks. Read the full whitepaper to discover the benefits of AI-powered change management.
-
Harnessing the Full Power of Analytics
By:
Type: Talk
Analytics in AI have enormous potential in the business world. From providing insights to maximise the value of data and business impact, to predictive analytics and data visualisations. The opportunities seem truly endless. However, many organisations struggle to capture the full value of AI and analytics. Leveraging analytics fully can be transformative for your business, which is why in this month’s episode of AI: The Future of Business, we’ll be exploring how you can take AI and analytics one step further and experience the transformative power of analytics. Join Ramesh Dontha and panellists as they discuss: - How to leverage the full potential of analytics - The top 5 business benefits of analytics - Different models of analytics, from predictive to prescriptive - What’s next in the world of analytics?
-
3 pro tips from ESG analysts on using GenAI
By: Enterprise Strategy Group
Type: ESG Infographic
To make sense of where tech buyers stand today, Enterprise Strategy Group (ESG) conducted a survey across 670 IT and business decision makers involved in GenAI initiatives. Download this ESG infographic to view the results, including GenAI research activity and 3 pro tips from our analysts on using GenAI.
-
The Forrester Wave™: End-User Experience Management Solutions, Q3 2024
By: Lakeside Software
Type: Analyst Report
Forrester recently identified the leading end-user experience management (EUEM) solutions. In this report, you’ll find out how Lakeside Software's comprehensive data and AI-powered analytics can provide complete visibility to proactively manage the digital employee experience. Read the full Forrester Wave report now to learn more.
-
AI + Data Predictions 2025: How Operationalizing AI Will Drive Technical Advances and Leadership Challenges
By:
Type: Video
Join Snowflake’s leading experts as they discuss the AI-accelerated future. They will share predictions about taking LLMs from inspiration to real value, adapting to an AI-powered workforce, securing AI in the enterprise, and more. Regardless of where you are in your data strategy, we have a number of conversations to help you get value from your data today and achieve generative AI preparedness tomorrow. This webinar covers upcoming trends across: - Observability - Autonomous agents - Governance - And more in the age of gen AI Prepare yourself and your team to tackle your 2025 data initiatives.
-
Discover how AI and connectivity shape enterprise networks by 2028
By: Comcast Business
Type: Analyst Report
IDC forecasts that by 2027, 75% of enterprises will use service provider AI and telemetry expertise to boost ESG use cases. The report highlights 10 key predictions for enterprise connectivity, focusing on AI, cloud-native networking, and edge computing. Read the full analyst report for detailed insights on future connectivity trends.
-
Data-driven decision making: Harnessing AI and ML for digital strategy
By:
Type: Talk
In the session, attendees will explore the critical role of data in shaping successful digital strategies and discover how AI and ML technologies can be utilized to extract meaningful insights. Topics covered include leveraging AI and ML algorithms for data analysis, real-time analytics, predictive modeling, customer segmentation, and targeting. The session also addresses challenges and ethical considerations in data-driven decision making and provides insights on integrating AI and ML into existing digital strategy frameworks. By attending this session, participants will gain the knowledge needed to leverage AI and ML for data-driven decision making, enabling them to develop effective digital strategies that drive business growth and success in today's competitive digital landscape. Key Topics: - Importance of data in shaping digital strategies. - Leveraging AI and ML for data analysis and insights. - Real-time analytics and predictive modeling for proactive decision making. - Optimizing customer segmentation and targeting using AI and ML. - Addressing challenges and ethical considerations in data-driven decision making. - Integrating AI and ML into digital strategy frameworks. - Exploring emerging trends and future directions in data-driven decision making.
-
Supercharging Customer Data with AI & ML To Power Predictive Insights
By:
Type: Replay
The field of AI & ML isn't new, yet marketers are still discovering new ways to apply these powerfully predictive methods on their large, complex and expanding data sets. Demand for data science talent continues to grow, but the problems of collecting and normalizing clean, meaningful data for machine learning are snowballing faster than most firms can respond. Join us to learn key strategies and innovative ways to supercharge your customer data with predictive insights to provide the best customer experience possible!
-
Infographic: Top 10 Technology Trends 2019
By: TechTarget ComputerWeekly.com
Type: eGuide
In this infographic, discover the top 10 technology trends for 2019 as predicted by Gartner. For digital-minded CIOs, Gartner's 2019 top 10 technology trends should come as no surprise: IT is getting smarter, casting an intelligent digital web over the enterprise -- and everywhere else.
-
Unlocking Operational Excellence in Process Manufacturing: The Role of AI and Advanced Analytics
By: Seeq
Type: White Paper
Process manufacturers struggle with quality issues, high scrap rates, and underutilized capacity. Advanced analytics and AI use time series data to optimize operations, enhance decision-making, and improve performance. Read this white paper to learn how these technologies drive continuous improvement without major capital investment.
-
Why data integrity is critical to the success of your AI initiatives
By:
Type: Replay
In the rapidly evolving landscape of AI, maintaining data integrity is critical. How much your organization benefits from its predictions is entirely dependent on the quality and accuracy of the data you’re feeding into it. That’s why prioritizing robust data integrity is non-negotiable for any organization investing in AI initiatives. Join us to hear about the data integrity practices that can help you unlock the full potential of AI while minimizing risks and ensuring responsible use. In this webinar you’ll learn: Why data integrity is crucial for AI How data integrity directly influences the success of AI initiatives The significance of high-quality and accurate data for training AI models How data integrity practices can help in minimizing biases and errors in AI outcomes Best practices for maintaining data integrity throughout the AI project lifecycle
-
Embracing or Bracing? Tech Buyers' Perceptions of AI-Generated Content
By: Enterprise Strategy Group
Type: ESG Infographic
With the demand for content higher than ever from B2B buyers, it’s no surprise that marketers are excited about the opportunity generative AI (GenAI) presents to ease the content creation burden. Yet with great new tools comes great responsibility – and the same is true for GenAI. Access this guide to learn more.