Modernize your data practices with DataOps, MLOps, and FinOps
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Navigate data challenges with modern data architecture strategies
By: Informatica
Type: White Paper
Modern data architectures are transforming how organizations leverage their cloud-based and on-premises data. This white paper explores three emerging patterns: the modern data stack (MDS), data fabric, and data mesh.
The MDS offers scalable frameworks for processing data from diverse sources. Data fabric uses AI to connect disparate data sources through active metadata. Data mesh supports decentralized, domain-oriented data ownership.
Key benefits include:
· Breaking down data silos
· Leveraging AI for knowledge graphs
· Democratizing data access
· Accelerating decision making
· Providing architectural flexibility
Learn how Informatica's IDMC supports these architectures in this white paper.
These are also closely related to: "Modernize your data practices with DataOps, MLOps, and FinOps"
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How real-time data transformed Yamaha's operations and CX
By: Informatica
Type: White Paper
Yamaha's "One Yamaha" initiative shows how unifying data across business units can transform operations and enhance customer experiences. By implementing Informatica's Intelligent Data Management Cloud (IDMC), the company successfully:
• Democratized real-time data access
• Transitioned to real-time processing, reducing errors
• Accelerated dealer operations and streamlined sales
• Integrated AWS cloud and Snowflake data warehouse
• Reduced IT costs with Informatica's IPU pricing modelResults: implementation in two months, improved agility, enhanced team collaboration, and better customer experiences.
Explore this white paper to learn how unified data management can transform your organization.
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5 best practices for making your organization's data AI-ready
By: Informatica
Type: White Paper
AI readiness requires strategic data management for relevant, responsible, and robust AI outcomes. This white paper explores key challenges data leaders face with GenAI initiatives:
• Data management: quality control, system integration, and scaling AI-ready data
• Governance and compliance: data classification, security protocols, and regulatory awareness
• Adoption strategies: workforce training, cultural resistance, and ROI expectationsSuccessful organizations see AI readiness as an ongoing investment needing:
• Technical expertise and management skills
• Data governance frameworks
• Clear business value metrics
• Strategic use case selectionRead this white paper for best practices.
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Navigating data management for compliant AI in a changing world
By: Informatica
Type: White Paper
As AI regulations evolve, organizations need strong data governance for compliance. This white paper outlines AI legislation, governance challenges, and principles for responsible AI. Discover how cloud-based data management aids compliance and innovation. Read the white paper to guide your responsible AI governance.
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How 5 key ways to build a modern data architecture deliver value
By: Informatica
Type: White Paper
Building a business case for modern data architecture involves quantifying benefits. This white paper explores five opportunities: improved developer efficiency, faster time to value, reduced platform administration, lower downtime costs, and enhanced flexibility. See how a common data platform drives quality and financial results.
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Unlocking AI data management strategies for superior experiences
By: Informatica
Type: White Paper
Learn how organizations like Holiday Inn Club Vacations and Discount Tire transformed customer experiences through AI-powered data management. Discover how they unified customer data, reduced duplicate records, and created 360-degree customer views to drive personalization, efficiency, and loyalty. Explore real-world AI-driven data strategies.
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The essentials of data management for responsible AI outcomes
By: Informatica
Type: White Paper
AI adoption is growing, raising concerns about ethical compliance. This guide examines responsible AI principles like fairness, transparency, and privacy. Learn how data governance frameworks and tools like Informatica IDMC help implement AI ethically. Discover ten key actions for building trust through responsible AI.
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Prepare your data architecture for the demands of generative AI
By: Informatica
Type: Infographic
Successful GenAI implementation requires addressing critical data challenges: data quality (42%), privacy and protection (40%), AI ethics (38%), sufficient domain-specific training data (38%), and AI governance (38%). View this infographic to learn how modernizing your data architecture can help overcome these challenges for GenAI success.
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Data strategy guidelines for AI: A practical guide for IT leaders.
By: Informatica
Type: Infographic
This infographic offers IT leaders a checklist of data requirements for implementing predictive and generative AI technologies. Discover key data considerations to ensure AI initiatives deliver business value. Review the infographic to build a solid foundation for your organization's AI strategy.
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Want a modern integration service that works?
By: Informatica
Type: Data Sheet
Many existing enterprise integration technologies are rigid, expensive to maintain, and too slow to respond to the requirements of your business. This white paper details Informatica’s Cloud Application Integration service, which offers a single, trusted solution to support any integration pattern, data set, or endpoint. Access it here.
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See how cloud data integration can deliver a 335% average ROI
By: Informatica
Type: White Paper
Informatica Cloud Data Integration customers achieved 335% ROI with a 5.3-month payback, realizing benefits like 67% faster data processing, 30% improved developer productivity, and streamlined integration. Organizations noted enhanced data quality crucial for AI. Read the white paper to see how cloud data integration can transform management.
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Focus: ERP in the cloud
By: TechTarget ComputerWeekly.com
Type: eGuide
In this guide we reflect on 50 years of business software followed by a look to the future as we explore the evolution from on-premise to cloud systems; analysing Oracle's claim for Infrastructure as a Service (IaaS) business to the proliferation of cloud integrations.
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What the future holds for cloud management in APAC
By: TechTarget ComputerWeekly.com
Type: eGuide
In this e-guide, we dish out useful tips from APAC organisations that have successfully migrated to the cloud, the thinking behind their approaches to cloud migration and what they are doing to not only keep the lights on, but also raise their game in areas such as cloud data management and cloud security.
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The Cloud Data Platforms Survey 25
By: Snowflake
Type: Research Content
This report highlights Snowflake Cloud Data Platform's top rankings in BARC's Cloud Data Platforms Survey for performance, scalability, and customer satisfaction. Key findings show high user satisfaction and recommendation rates. The study offers insights into Snowflake's market position and user experiences. Read the full report for analysis.
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How this data company solved its global tax management challenges
By: Oracle
Type: Case Study
Informatica partnered with Thomson Reuters ONESOURCE to enhance global tax data quality. This enabled centralization of indirect tax processes, reduced IT involvement, and improved visibility in tax determination across 30+ countries. ONESOURCE also identifies data entry errors and aids expansion. Learn how tax automation can transform compliance.
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Prepare your organization for AI success with the right foundations
By: Nexon
Type: Research Content
Australian organisations are evolving in AI readiness, with data maturity and infrastructure modernisation as key factors. Research shows 30% of companies now feel prepared for AI, up from 9% earlier in 2024. For SMBs and mid-market firms, strong data foundations are crucial for AI success in 2025. Read the report for comprehensive insights.
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Evaluate Gartner's latest augmented data quality vendor rankings
By: Informatica
Type: Gartner Magic Quadrant
The 2025 Gartner Magic Quadrant for Augmented Data Quality Solutions evaluates 12 vendors offering AI-powered tools to enhance data quality via automation. With 70% of organizations expected to adopt these solutions by 2027 for AI support, these tools are vital for AI-ready data. Review the Magic Quadrant to find the best vendor for your needs.
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Key vendors in Gartner's data and analytics governance report
By: Informatica
Type: Gartner Research Report
This Magic Quadrant evaluates data and analytics governance platforms for automating policy setting and enforcement. Leaders include IBM, Informatica, and Collibra, while Visionaries like Alation and dataworld show innovation. Key trends are convergence, consumerization, AI governance, and stewardship. Read this report to find the right platform.
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Data classification tools: What they do and who makes them
By: TechTarget ComputerWeekly.com
Type: eGuide
Data classification is an essential pre-requisite to data protection, security and compliance. Firms need to know where their data is and the types of data they hold. In this article, learn more about how these tools can help keep your data tidy and which suppliers offer the best options in the market.
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Data quality emerges from Covid-19 more critical than ever
By: TechTarget ComputerWeekly.com
Type: eGuide
In this e-guide: The public has been drenched in data during the Covid-19 pandemic. And the issue of the quality of that data has increasingly come to the fore.
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CASB, CSPM, CWPP Emerge as Future of Cloud Security
By: Palo Alto Networks
Type: eGuide
In this eguide, learn about the emergence and the future of Cloud security tools that will help bring successful and securely protected cloud environments.
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10 AI and machine learning trends
By: TechTarget ComputerWeekly.com
Type: eBook
Artificial intelligence technologies are transforming business processes and society at large. As enterprises expand the uses of AI, this field starts to move towards new domains, such as conceptual design, smaller devices and multi-modal applications. Here are 10 top 2022 trends IT leaders should prepare for now.
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Deep Dive into DataOps
By: TechTarget ComputerWeekly.com
Type: eGuide
In this e-guide, we hear from key decision-makers from Altran, Moogsoft, Puppet, Morpheus, Talend, NetApp and PagerDuty about how and why they are adopting DataOps.
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New Gartner Magic Quadrant for data integration tools released
By: Informatica
Type: Gartner Research Report
Gartner evaluates 20 top vendors in data integration tools, naming AWS, Denodo, Google, IBM, Informatica, Microsoft, Oracle, Qlik, and SAP as Leaders. The report examines capabilities for operational analytics and AI infrastructure across integration styles. Read this report to choose the right data integration solution for your needs.
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Computer Weekly – 6 September 2022: Out with the old at Asda
By: TechTarget ComputerWeekly.com
Type: Ezine
In this week's Computer Weekly, we talk to Asda's CIO Carl Dawson about the supermarket's cloud-oriented renovation of its technology stack. We narrate the security woes at Twitter. And we examine best practices for data backup. Read the issue now.
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A Computer Weekly buyer's guide to Business Intelligence and Analytics
By: TechTarget ComputerWeekly.com
Type: eGuide
Business intelligence and analytics is an ever-changing landscape. In this 20-page buyer's guide, Computer Weekly looks at firms' search for data scientists, how modern business intelligence works for big data and the role DevOps can play in navigating a data onslaught.
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Why DataOps is crucial for digital transformation success
By: HighByte
Type: White Paper
How can your business simplify data contextualization to maximize the value of your technology investments? By leveraging DataOps to define standard models and establish and manage integrations, operational teams can provide data to the systems and business users who are requesting it in a more efficient and managed way. Read on to learn more.
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Data Fabric For Dummies
By: Hitachi Pentaho
Type: eBook
In this digital edition of the popular For Dummies series of reference books, step into the world of data fabrics: inside, learn what a data fabric is and how to realize its benefits, how to effectively build and deploy a data fabric, best practices for optimizing and modernizing data access, and more.
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Data Fabric For Dummies
By: Hitachi Pentaho EMEA
Type: eBook
In this digital edition of the popular For Dummies series of reference books, step into the world of data fabrics: inside, learn what a data fabric is and how to realize its benefits, how to effectively build and deploy a data fabric, best practices for optimizing and modernizing data access, and more.
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Modern Industrial Data Architecture Best Practices
By: HighByte
Type: White Paper
Industrial DataOps is the dominant framework for mastering 4.0 data transformation projects, and it is key for leveraging solutions that can deliver data to users for a real-time view of the enterprise. Read on to learn about a solution that can help manage data in a common format that is ready to consume, contextualize, and scale for the customer.
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CW APAC: Expert Advice on data management
By: TechTarget ComputerWeekly.com
Type: Ezine
In this handbook, Computer Weekly looks at how companies and data management experts are tackling data challenges, and finds out how organisations are augmenting data management through artificial intelligence and machine learning.
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Computer Weekly 16 April 2019: Digital transformation at the Crown Prosecution Service
By: TechTarget ComputerWeekly.com
Type: Ezine
In this week's Computer Weekly, we examine how the Crown Prosecution Service is helping to digitally transform the UK justice system. We report from Google's cloud conference on the firm's plans to expand its presence in enterprise IT. And we look at the opportunities and challenges of using AI in the education sector. Read the issue now.
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Computer Weekly 5 March 2019: Modernising IT at the Bank of England
By: TechTarget ComputerWeekly.com
Type: Ezine
In this week's Computer Weekly, we talk to the Bank of England as it starts the modernisation programme for its core system. We look at the rise of DevSecOps and how it can help deal with increasingly complex security threats. And we examine the different approaches to storage for structured and unstructured data. Read the issue now.
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Data discovery: how to pick the right software
By: TechTarget ComputerWeekly.com
Type: eGuide
In this guide, we break down data discovery software by defining the categories, explaining the features and revealing the benefits. We also highlight the major players and products in an effort to inform buying decisions.
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Case Study: Southern Water's centralised data team geared for silo busting
By: TechTarget ComputerWeekly.com
Type: eGuide
Southern Water has centralised its data specialists and overhauled its data management and business intelligence technology to support business decision-making at scale
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How to effectively build and manage a UNS
By: HighByte
Type: White Paper
In this white paper, you’ll discover a software solution designed to provide organizations will all the necessary components to build and manage a Unified Namespace (UNS). Read on to learn how you can maximize the value and accessibility of your industrial data.
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10 steps to designing an industrial data architecture
By: HighByte
Type: eBook
In this interactive workbook, you’ll discover 10 steps accompanied by some brief questions that are designed to help industrial leaders learn how they can leverage data engineering strategies to get the most out of their data. Read on to learn how you can unlock hidden business value.
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Computer Weekly – 23 July 2024: Serving up a GenAI experience at Wimbledon
By: TechTarget ComputerWeekly.com
Type: Ezine
In this week's Computer Weekly, we go behind the scenes at Wimbledon to find out how technology is improving the tennis experience for fans. We talk to Meta's AI research chief about the challenges and opportunities of large language models. And we find out why cloud databases are becoming increasingly popular. Read the issue now.
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A Computer Weekly buyer's guide to data quality
By: TechTarget ComputerWeekly.com
Type: eGuide
The value of data depends on its quality. In this 14-page buyer's guide, Computer Weekly looks at how the coronavirus pandemic has highlighted the challenges of inaccurate datasets, the new analytics techniques improving data quality and Informa's use of Collibra software
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Ultimate Guide to MLOps: 78 Pages of Insights
By: DataBricks
Type: eBook
If you were to break down machine learning operations (MLOps) into a formula, this e-book by Databricks explains, it would the following: MLOps = DataOps + DevOps + ModelOps. Now that you know what MLOps is, why should you care about it? Find out in the 78-page ultimate guide.
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Energy Service Provider, VNG Handel & Vertrieb, Boosts Productivity and Cuts Storage Costs by 91% with Pentaho
By: Hitachi Pentaho
Type: Case Study
VNG Handel & Vertrieb, an energy service provider, boosted productivity and cut storage costs by 91% using Pentaho Data Integration. Read this case study now to learn how they streamlined data pipelines, handled large data volumes, and integrated systems to enhance the user experience.
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Energy Service Provider, VNG Handel & Vertrieb, Boosts Productivity and Cuts Storage Costs by 91% with Pentaho
By: Hitachi Pentaho EMEA
Type: Case Study
VNG Handel & Vertrieb, an energy service provider, boosted productivity and cut storage costs by 91% using Pentaho Data Integration. Read this case study now to learn how they streamlined data pipelines, handled large data volumes, and integrated systems to enhance the user experience.
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Bringing sustainability to your industrial data architecture
By: HighByte
Type: Blog
While industrial processes are a big contributor to a company’s CO2 emissions, data processing and storage is also an important part of the sustainability equation. Read on to learn how manufacturers can support their sustainability goals while potentially increasing production and why DataOps is crucial for success.
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It's complicated: how data integration lies at the heart of evermorecomplex data architectures
By: TechTarget ComputerWeekly.com
Type: eGuide
Data integration and preparation remains the knotty problem at the heart of many data management and business intelligence programmes.Demands on IT leaders in user organisations – especially large, complex ones – are and will continue to be equally complex and pressing as boards look to get business value from data. Read more in this e-guide.
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A Computer Weekly buyer’s guide to data visualisation
By: TechTarget ComputerWeekly.com
Type: Essential Guide
Data visualisation is proving its value throughout a period of economic uncertainty. In this 16-page buyer’s guide, Computer Weekly looks at the rise of embedded analytics, the advantages of real-time data and Siemens’ exploration of industrial metaverse use cases
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Insiders’ Guide to Self-Service Analytics
By: Insightsoftware
Type: White Paper
Self-service analytics are vital for how your users interact and engage with your application. This e-book describes the contrast in user experience between customizable self-service analytics and one-size-fits-all self-service analytics. Read on now to learn how you can improve the adoption and stickiness of your applications.
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Predictive analytics gains evermore accuracy in guiding enterprises forward
By: TechTarget ComputerWeekly.com
Type: eBook
Predictive analytics can help businesses look for meaningful patterns in data, then build models that forecast what is likely to happen in the future.
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How to get more out of your industrial data
By: HighByte
Type: White Paper
Although most industrial companies have been able to load their data in their Unified Namespace (UNS), many are finding that they are unable to use it effectively. In this white paper, you’ll discover how you can unlock the necessary capabilities to contextualize your data and maximize the value of your UNS. Read on to learn more.
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Business analytics needs underpinnings of sound data and data-skilled humans
By: TechTarget ComputerWeekly.com
Type: eBook
Data analytics for the solution of first-order business problems is probably more important than ever. It is not new. Companies and organisations have been analysing computerised data for many decades. But all sorts of companies now pronounce themselves "data driven". Read more about business analytics trends in this exclusive e-guide.