A Data Scientist's Guide to Saving Time
By: HP Inc View more from HP Inc >>
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How to easily get real-time analytics from Kafka
By: TIBCO
Type: eBook
Kafka use is skyrocketing with the rise in digital business applications, but many intelligence and management tools do not natively connect to Kafka.
Getting analytical insights from Kafka can require custom coding, complex developer components, and modified database and business intelligence tools. It’s not easy, not off-the-shelf, not real time, and not cheap.
But TIBCO has changed this. Now, analytics agility can be achieved in minutes with a native low-code, or in most cases, no-code Kafka connection from TIBCO.
Read how TIBCO can help implement a seamless Kafka connection for your enterprise, ensuring that your critical data is accessible where you need it, when you need it.
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A 9-Step Recipe for Successful Machine Learning
By: TIBCO
Type: White Paper
To make artificial intelligence (AI) and machine learning (ML) initiatives valuable to the entire organization, you need to deliver the insights they provide to the right person or system at the right time within the right context.
In this TIBCO white paper, follow this 9-step recipe for successful machine learning, which includes:
- Empowering various user types
- Collaborating across teams
- Using best practices and centers of excellent
- And more
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Machine learning at enterprise scale: Steps to success
By: O'Reilly
Type: eBook
According to a recent study, 56% of executives believe that machine learning will be of critical strategic importance to their business within the next 3 years. Machine learning is at the cutting edge of the current digital landscape, and as with anything that is evolving, it can be difficult to navigate.
In this e-book, O’Reilly has provided an intensive breakdown of how machine learning can be best implemented into an organization’s infrastructure. Using examples set by the industry’s foremost leaders and experts, this e-book highlights 6 commonly faced problems, and provides the knowledge and resources needed to overcome them.
Download the full e-book to learn how to best utilize machine learning.
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Build an effective AI strategy: Overcome 4 common adoption challenges
By: Google Cloud
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Improving decision-making, customer experience, and innovation requires faster data insights. AI and ML increase the value of data by rapidly identifying patterns that are either impossible or too time-consuming to see with manual analysis. Gain more value from your data: Build an effective AI strategy. Read on to learn more.
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Red Hat OpenShift Data Science EN-DSC CS-1
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Explore this product overview to learn how Red Hat OpenShift Data Science gives data scientists and developers a powerful AI/ML platform for building and deploying intelligent applications all in one place.
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E-Guide: Selecting a SIM for midmarket business
By: TechTarget Security
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This expert E-Guide discusses the evolvement of SIM tools, differences in deployment processes and top requirements you should consider before making a decision.
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Leveraging data to support business decision-making
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To deliver ROI on data science investments, companies must be able to scale data initiatives across the enterprise. Read this e-book to learn how you can turn data into insights at scale across your organization.
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Become a Data Science Superhero in 6 Easy Steps!
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Read this e-book to discover 6 top skills you need to set yourself apart as a data scientist and how to hone them.
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Top 5 ways developers and data scientists can collaborate EN-DSC CS-8
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As a developer, you need to be able to collaborate seamlessly with your data science colleagues to work with them to build effective AI-based applications. Access this whitepaper for a checklist of the top 5 ways developers and data scientists can collaborate to make the most of your AI investments.
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5 Graph Data Science Basics Everyone Should Know
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Graph data science brings together graph analytics, statistics, and AI and ML techniques to improve their predictive and prescriptive models. This white paper walks you through 5 graph data science basics so you can feel confident knowing when to use it in your daily work. Access it here.
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Detect anomalies in manufacturing with machine learning
By: TIBCO
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Read this white paper to learn about a multivariate machine learning solution that has been developed for semiconductor customers using the TIBCO Connected Intelligence Platform.
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Top 5 considerations for your AI ML platform EN-DSC CS-4
By: Red Hat
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Artificial intelligence (AI) and machine learning (ML) are essential for today’s organizations. But there is still a lack of collaboration involved in the development of AI and ML applications. Download this checklist to learn 5 considerations needed to implement MLOps processes that help teams create data-driven applications for your business.
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Tidy data: Reducing complexity
By: LiveAction
Type: White Paper
Data Scientists estimate that they spend 80% of their time finding and cleaning data, according to a recent report. Access this white paper to learn common actions for tidying data and how you can reduce complexity.
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47-page e-book: Ultimate playbook for scaling AI
By: Dataiku
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This 47-page e-book presents the part different people or roles must play in organizational transformation, providing tips, keys to success and real-life stories about scaling AI efforts for each. Read on to learn how your organization can become more efficient in your efforts to scale AI initiatives across the enterprise.
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Web Browser Security Features Make Attacks Harder
By: TechTarget Security
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This e-guide from SearchSecurity.com explores the features Microsoft Internet Explorer, Mozilla Firefox, and Google Chrome are developing that are making the job of the attacker much harder.
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Explore the tangible benefits of HPE Ezmeral Data Fabric
By: Hewlett Packard Enterprise
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HPE Ezmeral Data Fabric allows a digital transformation from edge to cloud. Here are some global enterprises who utilised Ezmeral to provide better analytics, detect anomalies and attacks, and support analytics as a service. Read on to discover more benefits these organisations saw from Ezmeral, including over $6 million in savings.
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19 machine learning interview questions and answers
By: TechTarget ComputerWeekly.com
Type: eGuide
Aspiring machine learning job candidates should be fluent in varied aspects of machine learning, from statistical theory and programming concepts to general industry knowledge. Read our list of commonly asked machine learning questions and accompanying answers to help you prepare for your interview.
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Operationalizing manufacturing with ML and digital twins for rapid insight
By: TIBCO
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Machine learning (ML) models are immensely useful tools for organizations seeking to build and understand digital twins for their real-life manufacturing processes. Read on to learn how you can quickly optimize manufacturing processes and provide your company with valuable real-time insight on your equipment and processes.
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Top New Year’s Resolutions for Data, Analytics & AI
By: Dataiku
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Deloitte’s “State of AI in the Enterprise” report cited that, despite increased deployment activity, outcomes from AI are lagging and organizations are seriously struggling to drive results. Read on to learn about the top 5 challenges for successful AI implementation and how you can address them to increase productivity and improve decision making.
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Why 87% of AI & ML projects fail
By: Comet
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Despite significant progress in the machine learning and AI space, implementing scalable teams, frameworks and processes still presents critical challenges. Explore this e-book to learn the critical requirements for an effective machine learning team that will give your company a competitive advantage as the machine learning and AI space evolves.
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The Complete Buyer's Guide for a Semantic Layer
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Read on to discover the 10 things a buyer needs to consider when buying a semantic layer, including consumption style flexibility, query performance and caching options, and security and governance requirements.
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How AI can benefit insurance companies
By: TIBCO
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The insurance industry is rapidly transforming; with the advent of AI and machine learning, much of the risk assessment and day-to-day business process can be automated. Read this white paper to learn how TIBCO’s data science and AI platform can integrate with a variety of existing features improve your data science initiatives.
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Data Fabric as Modern Data Architecture
By: TIBCO
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While most organizations acknowledge the importance of data in driving positive outcomes and have embraced digital transformation efforts, far fewer have actually succeeded in building data-driven organizations. Access this O’Reily e-book, courtesy of TIBCO, to learn more about building and using a data fabric.
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Transform Customer Data into Predictive Insights with AI
By: mParticle
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Several issues can prevent growth teams from adopting AI, including a lack of data science resources and no unified view of the customer. Read on to learn how adopting an AI customer data platform (CDP) can help you enable your organization with the capabilities needed to effectively leverage AI insights.
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NetApp For Healthcare and Life Sciences: Serving Data at Life-Saving Speed
By: NetApp
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Check out this e-book for the 3 trends making waves in the healthcare and life sciences industry, and discover the data management solutions that can help support the corresponding influx of data.
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Graph data science: Find connections between data points
By: Neo4j
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How can you enable your organization to use the relationships in your data to put data in context and answer pressing questions? Access this white paper to learn how your data scientists can leverage graph data science to explore billions of data points in seconds and identify hidden connections that lead to better stakeholder decision making.
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Data Exploration and Discovery: A New Approach to Analytics
By: Teradata
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Access the following white paper to uncover how when used in conjunction with analytics, exploration and discovery tools can give you access to better decision making capabilities, lower operational costs, and an improved business process overall.
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Top considerations for building a production-ready AI ML environment EN-DSC CS-12
By: Red Hat
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By building AI, ML, and deep learning into your software applications, you can achieve measurable business outcomes including better customer satisfaction, automation across operations, and higher revenue. Access this white paper to learn the 6 steps of the AI/ML life cycle and learn how you can create a production-ready AI environment.
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How to successfully deploy flexible AI insurance pricing models
By: TIBCO
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Read this solution brief to learn how TIBCO Model Ops helped an auto insurance unit develop, deploy, and operationalize a successful AI-powered dynamic pricing system.
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Thinking Smarter: How TIBCO & AWS Put You on The Path To AI-Informed Decisions and Faster, Better Outcomes
By: TIBCO
Type: White Paper
With a single decision environment for diagnostic, predictive, and real-time analytics, static point-in-time reporting generated from traditional BI tools is transformed into a hyper-aware nerve center for rapid learning. Read this whitepaper and learn how to make AI-informed decisions and adapt to market changes in real time.
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Survey report: Real AI/ML use cases
By: TIBCO
Type: White Paper
In the business world, it’s not always crystal clear where AI and machine learning are generating value. Inside this snapshot, see the results of a survey designed to pinpoint current business use cases of AI models – and find out which AI uses are poised to see the most growth.
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The Better Way: A Hyperconverged Analytics Platform
By: TIBCO
Type: White Paper
Your BI applications may risk falling prey to “zombie analytics”: dashboards that lack prescriptive (or even timely) insights, mindlessly undermining business intelligence. Check out TIBCO's guide and learn how hyperconverged analytics platforms ensure your insights are more than hindsight views.
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RPA vs. AI: Powerful apart, even more powerful together. Here’s why.
By: UiPath
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While RPA can capture data and manipulate apps, the more complex and advanced tasks were previously out of reach. That is where AI comes into play. Open up this white paper to take a closer look at the challenges and benefits of applying AI to automation, as well as suggestions for how to get started bringing the two together in your organization.
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Modern Analytics Platforms
By: TIBCO
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In today’s dispersed workforce, data analytics is a key role in measuring your organization’s agility. Download this e-book to explore how you can begin your journey to enterprise agility via modern analytical strategies, use cases and more.
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Red Hat OpenShift Data Science EN-DSC CS-15
By: Red Hat
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Tap into this product overview to learn how OpenShift Data Science is helping data scientists rapidly develop, train, test and deploy ML models in the cloud without infrastructure concerns or cloud-specific vendor lock-in.
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Accelerate your decision-making with hyperconverged analytics
By: TIBCO
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Based on powerful diagnostic, predictive, and real-time analytics, hyperconverged analytics transform traditional rearview monitoring into a rapid learning, decision-driven, and actionable environment. Find out how hyperconverged analytics can amplify and accelerate your enterprise's decision-making with TIBCO’s guide.
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Accelerate your ML development process with proper evaluation
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Process challenges are creating friction in machine learning - in a recent survey of over 500 ML practitioners, 68% admitted abandoning 40-80% of their experiments in the past year. Read on to learn about 3 characteristics ML practitioners should consider when evaluating tools to reduce friction and accelerate the ML development process.
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Developing a comprehensive advanced analytics and AI strategy
By: Hewlett Packard Enterprise
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AI adoption is one of the highest priorities for the C-Suite, but the reality of AI today is less flashy than the “AI-first” hype. Explore this interactive white paper to learn how you can successfully navigate the evolving AI landscape by avoiding common pitfalls and developing a clear, aligned tech and data strategy.
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24 reasons to power your trading analytics future with KX
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How can you enable your organization to produce and deliver timely analytics and actionable insights? With KX you can manage, analyze, enrich and visualize all your target data on a unified platform. Read on to learn about 24 reasons to power your trading analytics future with KX and make better-informed business decisions.
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Exploring new web browser security capabilities
By: TechTarget Security
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New threats are created on a regular basis and businesses need to be prepared for the risks. View this expert E-Guide to explore some of the new security capabilities of web browsers and how they help prevent attacks. Learn more about the features that strengthen the security of Web gateway's by consulting this asset.
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Realizing the Potential of AI in the Retail Industry
By: NVIDIA VMware
Type: eBook
How can you overcome the obstacles of AI adoption such as incompatible infrastructure and data silos? Read on to learn how you can leverage the AI-Ready Enterprise Platform from VMware and NVIDIA to deliver simplicity and scalability for your AI workloads and fuel improved business insights.
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Unlock the full potential of your medical research
By: Hewlett Packard Enterprise
Type: Webcast
How can you enable your data science teams to focus on advancing medical discoveries instead of dealing with lengthy, manual tasks? Watch this webcast to learn how you can enable faster insights with the HPE GreenLake for Flywheel solution, a robust ML AI data management platform that frees organizations from burdensome IT tasks.
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Unix-to-Linux Migration
By: TechTarget Data Center
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Get a step-by-step approach for data center managers that covers everything from making the business case to getting the best training. Sections in this IT Handbook include training staff to manage linux environments and much more.
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What Every Operations Executive Should Know About the Power of Continuous Intelligence
By: TIBCO
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Continuous intelligence, the practice of actively integrating up-to-date, real-time data across an enterprise, is a top priority for a growing number of COOs and CEOs. But what exactly is it? And how does a business institute it? Read on to learn more about continuous intelligence and its 10 essential components.
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How semantic layers are changing in the context of better analytics
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The explosion of analytics possibilities and methods means that coupling a semantic layer to one analytics style no longer makes sense—in fact, some decoupled semantic layer approaches can improve data quality and foster self-service analytics. Access this e-book to learn how you can best deploy semantic layers for your analytics.
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4 ways quants can improve their data analytics ecosystem
By: KX
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How can you harness data across the business more efficiently to deliver better research outcomes? Read on to learn how to overcome 4 key challenges to optimize your data analytics ecosystem, including fragmented data, slow data processing, eliminating batch delays and 1 more.
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How augmented intelligence reduces the chasm between data and decision-making
By: Fosfor
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Warehouse operations have grown increasingly more complex over the last decade. This white paper details how augmented intelligence can help transform your warehouse operations for the better by allowing you to freely explore insights, spend time diagnosing issues and more. Access it here.
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How to leave traditional BI in the dust with hyperconverged analytics
By: TIBCO
Type: White Paper
Traditional BI cannot keep pace with data science-infused advanced analytics, and those who cling to familiar but outdated methodologies are destined to fall behind. Hyperconverged analytics integrates data science and cutting-edge analytics, allowing organizations to meet these data and insight challenges head on. Read on to learn more.
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The Business Impact of Using a Semantic Layer for AI & BI
By: AtScale
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Read this e-book to understand the true business impact of a semantic layer and how you can use one to improve time to actionable insights, while increasing scale and reducing costs of analytics deployment.
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Data Mesh And Its Impact On Data Platform Providers
By: Fosfor
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Both data lakes and a data warehouse have multiple limitations that cause bottlenecks for data teams. This white paper explores the paradigm shift to a data mesh approach, looking at the 4 principles of this architecture and how it makes data management easier. Access the white paper.