Customer Case Studies of Self-Service Big Data Analytics

Data is the future of business. Either take advantage of it, or get surpassed by those who do. In this webinar, Ovum's Tony Baer discusses the importance of building a modern data strategy that ensures your journey with Apache Hadoop and big data is a successful one. Together, we'll walk through how to build a plan for long-term success while realizing short-term gains, including: How to pinpoint the business goals that matter most How to assess your strengths and weaknesses to meet those goals How to build a thoughtful approach that ensures your initiatives succeed

Modernizing Architecture for a Complete Data Strategy

In Big Data projects, analysts often spend 80% of their time preparing data for analysis. In addition, users don’t have a good understanding of their data quality. Today there are multiple tools that assist with integration, data preparation, analysis and visualization. However, data quality continues to be one of the biggest challenges businesses face when deploying big data analytics. People need to profile their data and ensure data quality to get accurate insights and make informed business decisions. Join Datameer as we address these pain points with visualizations at every step. This webinar will highlight and showcase: -How visual data profiling reduces the guesswork in the data wrangling process -Enhanced interactive data mining capabilities reduce time to insight -A demonstration of the new 4.0 features and functions

Webinar - Introducing Datameer 4.0: Visual, End-to-End

Today, leading organizations struggle to make their data scientists productive in their modern data platforms. Data scientists find it difficult to use their existing open source languages (e.g. Python, R) and libraries with Hadoop, especially when the clusters are secured with Kerberos. At the same time, IT doesn't want to give special access to these users, who require very diverse and specific environment configurations to run their experiments. As a result, most data science teams work away from the big data cluster, often on their laptops or in other data silos. The negative business impacts are a lack of insight and agility for the most advanced users, and the security, governance, and cost issues that arise from data silos.

Unlocking data science in the enterprise - with Oracle and Cloudera

Join industry superstars Mike Olson (Cloudera CSO and co-founder) and Jim Curtis (451 Research senior analyst) as they outline the best practices for cloud-based machine learning and analytics in this “can’t miss” webinar. Hot topics include: Why enterprises are moving their analytics to the public cloud How to select the best cloud deployment model Design tricks that make cloud economics work Success stories, cautionary tales, and lessons learned James will share 451 Research findings and offer insights learned from surveying both the vendor landscape and enterprise practitioners. . Mike will regale you with his vision for the future of multi-disciplinary machine learning and analytics in hybrid- and multi-cloud environments 3 things to learn: Why enterprises are moving their analytics to the public cloud How to select the best cloud deployment model Design tricks that make cloud economics work

Optimize your cloud strategy for machine learning and analytics

Data volumes have experienced explosive growth in recent years, and that data is being generated from sources that are increasingly complex and varied. Harnessing and refining value from this data requires a new approach as data extraction, transformation, and loading (ETL) becoming increasingly more costly and difficult to scale. Organizations are looking to leverage Hadoop as an enterprise data hub—also called a “data lake” or “data reservoir”—as a key component of their data architecture to augment their data warehouse, ETL and analytical systems in order to maximize their existing investments, reduce costs, and unlock new business value from their data. In this webinar, you will learn: Real-world examples that illustrate why Hadoop is the best low-cost data hub, data lake, or data landing zone (staging area) option for ETL processing Proof points that demonstrate advantages of Hadoop and its ability to scale to manage increasing data volumes and support exploratory big data analytics Proven best practices for a cost-effective, reliable way to implement a data management platform for your entire big data analytical ecosystem Hidden issues to be aware of in deploying your data hub/data lake

MapR Enterprise Data Hub Webinar w/ Mike Ferguson

MapR Technologies

Government agencies are collecting and producing data at an accelerating rate, and constituents want access to this data with decreasing latency. Meeting a digitally savvy polity's desire for data while ensuring that data is open, accessible, and interpretable by all comes with unique challenges. I'll share some of these while walking through how governments are building their own data products using open data as well as empowering civic hackers. I'll also walk through why data science at the government level is fundamentally different than data science in the private sector.

Digital Government: Data + Government Isn't Enough | Wrangle Conference 2017

Big data analytics is revolutionizing the way businesses are collecting, storing, and more importantly, analyzing data. However, the adoption of a big data analytics solution has its share of failures and false starts. Watch this webinar to learn how to navigate the most common obstacles of big data analytics. Datameer and MapR have worked with customers to identify and solve the common pitfalls organizations face when deploying Hadoop-based analytics. In this webinar, we will show you how to: • Find the balance between infrastructure and business use cases • Overcome challenges of using multiple tools that address big data analytics • Leverage all your resources (data scientists, IT and analysts) most effectively

How to Avoid Pitfalls in Big Data Analytics Webinar

According to Forrester Research, only 22% of companies are currently seeing a significant return from data science expenditures. Most data science implementations are high-cost IT projects, local applications that are not built to scale for production workflows, or laptop decision support projects that never impact customers. Despite this high failure rate, we keep hearing the same mantra and solutions over and over again. Everybody talks about how to create models, but not many people talk about getting them into production where they can impact customers. Harvinder Atwal offers an entertaining and practical introduction to DataOps, a new and independent approach to delivering data science value at scale, used at companies like Facebook, Uber, LinkedIn, Twitter, and eBay. The key to adding value through DataOps is to adapt and borrow principles from Agile, Lean, and DevOps. However, DataOps is not just about shipping working machine learning models; it starts with better alignment of data science with the rest of the organization and its goals. Harvinder shares experience-based solutions for increasing your velocity of value creation, including Agile prioritization and collaboration, new operational processes for an end-to-end data lifecycle, developer principles for data scientists, cloud solution architectures to reduce data friction, self-service tools giving data scientists freedom from bottlenecks, and more. The DataOps methodology will enable you to eliminate daily barriers, putting your data scientists in control of delivering ever-faster cutting-edge innovation for your organization and customers.

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PRGX is the world's leading provider of accounts payable audit services and works with leading global retailers. As new forms of data started to flow into their organizations, standard RDBMS systems were not allowing them to scale. Now, by using Talend with Cloudera Enterprise, they are able to acheive a 9-10x performance benefit in processing data, reduce errors, and now provide more innovative products and services to end customers. Watch this webinar to learn how PRGX worked with Cloudera and Talend to create a high-performance computing platform for data analytics and discovery that rapidly allows them to process, model, and serve massive amount of structured and unstructured data.

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Machine learning and artificial intelligence can change the world. Diagnosing heart disease. Detecting fraud. Predicting insurance claims. Revolutionizing agriculture. In business, machine learning and artificial intelligence drive new sources of revenue and lower costs. But executives struggle to define an investment strategy. Researchers introduce innovations in machine learning daily. Technical jargon is opaque. Vendor hype muddies the waters. Industry analysts cover the field, but only at a high level. Cloudera Fast Forward Labs accelerates your machine learning journey. We deliver a unique blend of applied research and hands-on explanations that you can apply to your business today. In this webinar you will: Meet the Cloudera Fast Forward Labs team Cut through machine learning hype Explore recent examples of applied research See exciting new ML techniques Hear how machine learning is delivering real business value on multiple use cases 3 things to learn: Explore recent examples of applied research See exciting new ML techniques Hear how machine learning is delivering real business value on multiple use cases

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New research shows that 57% of the buying cycle is completed before a prospect even speaks to a company. Marketers already know this, Ninety-six percent (96%) of organizations believe that email personalization can improve email marketing performance. But where do we get this increasingly personal direction? The answer is likely in your customer data. In order to understand your customer needs contextualized in the moment they feel the need to act you will require a platform that can leverage real-time data. Apache Kudu is a Cloudera component that makes dealing with quickly changing data fast and easy. Companies are leveraging next generation data stores like Kudu to build data applications that deliver smart promotions, real-time offers, and personalized marketing. Join us as we discuss modern approaches to real-time application development and highlight key Cloudera use cases being powered by Cloudera’s operational database.

The Big Picture: Real-time Data is Defining Intelligent Offers

Title DataOps, the secret weapon for delivering AI, data science, and business intelligence value at speed. Synopsis ● According to recent research, just 7.3% of organisations say the state of their data and analytics is excellent, and only 22% of companies are currently seeing a significant return from data science expenditure. ● Poor returns on data & analytics investment are often the result of applying 20th-century thinking to 21st-century challenges and opportunities. ● Modern data science and analytics require secure, efficient processes to turn raw data from multiple sources and in numerous formats into useful inputs to a data product. ● Developing, orchestrating and iterating modern data pipelines is an extremely complex process requiring multiple technologies and skills. ● Other domains have to successfully overcome the challenge of delivering high-quality products at speed in complex environments. DataOps applies proven agile principles, lean thinking and DevOps practices to the development of data products. ● A DataOps approach aligns data producers, analytical data consumers, processes and technology with the rest of the organisation and its goals.

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Informatica is now part of the Business Data Lake ecosystem developed by Capgemini and Pivotal. Customers worldwide will now be able to leverage Informatica’s data integration software in addition to Pivotal’s advanced big data, analytics and application software, and Capgemini’s industry and implementation expertise. Informatica will deliver certified technologies for Data Integration, Data Quality and Master Data Management (MDM) to help enterprises distill raw data into actionable insights. http://www.capgemini.com/resources/the-business-data-lake-delivering-the-speed-and-accuracy-to-solve-your-big-data-problems

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Traditional Business Intelligence (BI) systems provide various levels and kinds of analyses on structured data but they are not designed to handle unstructured data. For these systems Big Data brings big problems because the data that flows in may be either structured or unstructured. That makes them hugely limited when it comes to delivering Big Data benefits. The way forward is a complete rethink of the way we use BI - in terms of how the data is ingested, stored and analyzed. More information: http://www.capgemini.com/big-data-analytics/pivotal

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Imagine being able to use insights about your customer acquisition journey to design campaigns that improve conversion rates. What if you could identify points of failure along the customer acquisition path or during product usage? Today more than ever the role of the marketing and product executives have become data-driven. Business executives who leverage data to understand prospect and customer behavior have gained an edge over their peers. Big Data analytics is the key to unlocking insights from your customer behavior data and empowers you to combine and analyze all of your customer interaction data to drive customer acquisition and loyalty.

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Adam Gugliciello, a 15-year veteran in Software Engineering and Systems Architecture specializes in highly available, parallel systems. In this session, we will answer common questions and demonstrate use cases on how Hadoop and Datameer help with asset management and risk management, fraud detection and data security. This presentation was given on January 24th at the CME Group's offices in Chicago, IL.

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Learn how organisations are able to drive better business outcomes from big data products and in turn, deliver personalised, real-time experiences to customers. We will walk through a common customer journey and demonstrate how to quickly test ideas and gather insights from data lakes, data pipelines, and sandboxes. See how to serve the needs of your business users, business analysts, and data scientists using AWS services for analytics, Big Data, and Machine Learning. Speaker: Vicky Falconer, Business Development Manager - Big Data, AWS

Better Business from Exploring Ideas - Modern Data Architectures on AWS

Better Business from Exploring Ideas - Modern Data Architectures on AWS In this session you will learn how organisations are able to drive better business outcomes from products and deliver more personalised and real-time experiences to customers. We will walk through a common customer journey that shows how to quickly test ideas and get insights, built on top of data lakes, data pipelines, and sandboxes using the same platform advantages of Modern Data Architectures on AWS as some of our most prominent customers. See how to serve the needs of your business users, business analysts, and data scientists using AWS services for analytics, Big Data, and Machine Learning. Craig Stires, APAC Head of Analytics, Big Data, and AI, Amazon Web Services

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http://www.datameer.com With data scientists in short supply, it’s surprising that much of their precious time is spent doing ”data plumbing”—preparing data or servicing business users rather than doing actual data science. Hadoop and self-service Smart Analytics is changing this reality. Join Matt Schumpert, Director of Solution Engineering at Datameer, as he walks through a real-world use case and discusses the evolution toward self-service data science, freeing data scientists to the hard work we so badly need.

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Watch the recorded event at: http://info.datameer.com/Slideshare- Economics-SQL-Hadoop.html As organizations clamor to utilize their new investments in Hadoop ecosystems AND leverage their existing analytical infrastructures, many rush to integrate SQL as a data access layer to leverage existing skill sets and get started faster. However, this approach relegates Hadoop to a data management and processing platform rather than the storage and compute engine optimized for analytical workloads it was purpose-built to be. These slides by EMA and Datameer, will discuss the technical limitations of SQL on Hadoop and propose alternative ways to fully maximize Hadoop investments. You will understanding: *how SQL negates the inherent benefits of Hadoop *why technological paradigm changes can sometimes be good *use cases when SQL on Hadoop makes sense

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Big Data enables you to combine the vast amount of customer behavior data being generated from mobile, web, social media, transaction systems, Ads and turn them into new insights that drive customer acquisition and retention. This talk will highlight and showcase how leading edge companies are leveraging big data to: Combine customer interaction data to understand customer buying journey Understand high-value customer behavior beyond profile segmentation Identify the most common path to customer churn Perform market basket analysis to help with cross-sell and up-sell Speakers: Matt Schumpert Director of Product Management Matt has been working in the enterprise infrastructure software space for 15 years in various capacities, including product management, sales engineering, sales leadership and strategic alliances. An early employee of Big Data pioneer Datameer, Matt is currently focused on driving the strategic direction and technology strategy for Datameer’s flagship Big Data analytics product. Previously, Matt built the sales engineering organization at Datameer, managed strategic partnerships at Oracle & BEA Systems in the US an Europe, and drove sales of business rules management software at ILOG (now IBM). Matt holds a BS in Computer Science from the University of Virginia.

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Banks are rich in valuable data and can build and maintain a competitive advantage by identifying and executing on high-value machine learning projects leveraging the rich data available.This webinar will describe use cases fit for big data and machine learning in the banking sector (commercial, consumer, regulatory, and markets) and the impact they can have for your organization. 3 things to learn: * How to create a next generation data platform and why it is important * How to monetize big data using predictive modeling and machine learning * What is needed for automated machine learning as a sustainable, cost-effective, and efficient solution

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The Increasing Criticality of MDM for Personalization for Customers and Employees Master data management seems to be one of those perennial, evergreen programs that organizations continue to struggle with. Every couple of years people say, “we're going to get a handle on our master data” and then spend hundreds of thousands to millions and tens of millions of dollars working toward a solution. The challenge is that many of these solutions are not really getting to the root cause of the problem. They start with technology and begin by looking at specific data elements rather than looking at the business concepts that are important to the organization. MDM programs are also difficult to anchor on a specific business value proposition such as improving the top line. Many initiatives are so deep in the weeds and so far upstream that executives lose interest and they lose faith in the business value that the project promises. Meanwhile frustrated data analysts, data architects and technology organizations feel cut off at the knees because they can't get the funding, support and attention that they need to be successful. We've seen this time after time and until senior executives recognize the value and envision where the organization can go with control over its data across domains, this will continue to happen over and over again. Executives all nod their heads and say “Yes! Data is important, really important!” But when they see the price tag they say, “Whoa hold on there, it's not that important”. Well, actually, it is that important. We can't forget that under all of the systems, processes and shiny new technologies such as artificial intelligence and machine learning lies data. And that data is more important than the algorithm. If you have bad data your AI is not going to be able to fix it. Yes there are data remediation applications and there are mechanisms to harmonize or normalize certain data elements. But looking at this holistically requires human judgment: understanding business processes, understanding data flows, understanding dependencies and understanding of the entire customer experience ecosystem and the role of upstream tools, technologies and processes that enable that customer experience. Until we take that holistic approach and connect it to business value these things are not going to get the time, attention and resources that they need. Seth Earley, Founder & CEO, Earley Information Science Dan O'Connor, Senior Product Manager at inriver

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With the ease and convenience of the internet, shopping online has never been faster and simpler than with a click of a button. But with this convenience, lurks the consequence for online fraud. Companies and merchants lose valuable time and money to online thieves scamming the web. Learn how to identify patterns with Datameer and Trustev as they demonstrate how to take control of the situation and combat combat against suspicious activity by using big data analytics. In this webinar, you will take away: *An understanding of the complexities and challenges of online fraud today *Best practices for merchants and companies to protect themselves from fraud *A demonstration of fraud reporting, prevention and prediction

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How do you protect the data in big data analytics projects? As big data initiatives focus on volume, velocity or variety of data, often overlooked in the big data project is the security of the data. This is especially important for financial services, healthcare and government or anytime sensitive data is analyzed. This webinar highlights: *Hadoop security landscape *Hadoop encryption, masking, and access control *Customer examples of securing hadoop environments

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You can view the full presentation of this webinar here: http://info.datameer.com/Slideshare-Fighting-Fraud-this-Holiday-Season.html In 2012, retailers lost $3.5 billion in revenue to online fraud. These losses spike by a substantial estimated 20% during the holiday season. Join Datameer and Hortonworks in this webinar to learn how Big Data Analytics can be used to identify new fraud schemes during peak fraud season. In this webinar, you will learn about: current challenges in identifying fraud what to look for in a big data solution addressing fraud how big data analytics can identify credit card fraud best practices

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To view the full webinar, please go to: http://info.datameer.com/Slideshare-Complement-Your-Existing-EDW-with-Hadoop-OnDemand.html With 40% yearly growth in data volumes, traditional data warehouses have become increasingly expensive and challenging. Much of today’s new data sources are unstructured, making the structured data warehouse an unsuitable platform for analyses. As a result, organizations now look at Hadoop as a data platform to complement existing BI data warehouses, and a scalable, flexible and cost-effective solution for data storage and analysis. Join Datameer and Cloudera in this webinar to discuss how Hadoop and big data analytics can help to: -Get all the data your business needs quickly into one environment Shorten the time to insight from months to days Extend the life of your existing data warehouse investments Enable your business analysts to ask and answer bigger questions

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Watch this recording at: http://info.datameer.com/Online-Slideshare-Lean-Production-Meets-Big-Data.html Sensor and robotic data will usher in a new wave of big data opportunities and use cases in 2014. This will be especially true in manufacturing as economic pressure to continuously improve operational efficiencies continue to challenge the bottom line. Join Lean Production Expert Conny von Ludwig (former Porsche Consulting & Lufthansa), and Datameer CEO, Stefan Groschupf as they discuss: -the current manufacturing challenges and how big data analytics can improve these inefficiencies -how to reduce production outages by 10% -a next gen big data analytic use case focused on manufacturing sensor data

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From Event to Action: Accelerate Your Decision Making with Real-Time Automation

Safe Software

MySQL Webinar, presented on the 25th of April, 2024. Summary: MySQL solutions enable the deployment of diverse Database Architectures tailored to specific needs, including High Availability, Disaster Recovery, and Read Scale-Out. With MySQL Shell's AdminAPI, administrators can seamlessly set up, manage, and monitor these solutions, ensuring efficiency and ease of use in their administration. MySQL Router, on the other hand, provides transparent routing from the application traffic to the backend servers in the architectures, requiring minimal configuration. Completely built in-house and supported by Oracle, these solutions have been adopted by enterprises of all sizes for their business-critical applications. In this presentation, we'll delve into various database architecture solutions to help you choose the right one based on your business requirements. Focusing on technical details and the latest features to maximize the potential of these solutions.

Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...

Miguel Araújo

Heather Hedden, Senior Consultant at Enterprise Knowledge, presented “The Role of Taxonomy and Ontology in Semantic Layers” at a webinar hosted by Progress Semaphore on April 16, 2024. Taxonomies at their core enable effective tagging and retrieval of content, and combined with ontologies they extend to the management and understanding of related data. There are even greater benefits of taxonomies and ontologies to enhance your enterprise information architecture when applying them to a semantic layer. A survey by DBP-Institute found that enterprises using a semantic layer see their business outcomes improve by four times, while reducing their data and analytics costs. Extending taxonomies to a semantic layer can be a game-changing solution, allowing you to connect information silos, alleviate knowledge gaps, and derive new insights. Hedden, who specializes in taxonomy design and implementation, presented how the value of taxonomies shouldn’t reside in silos but be integrated with ontologies into a semantic layer. Learn about: - The essence and purpose of taxonomies and ontologies in information and knowledge management; - Advantages of semantic layers leveraging organizational taxonomies; and - Components and approaches to creating a semantic layer, including the integration of taxonomies and ontologies

The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf

Enterprise Knowledge

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Maria Levchenko

Choosing the right accounts payable services provider is a strategic decision that can significantly impact your business's financial performance and operational efficiency. By considering factors such as expertise, range of services, technology infrastructure, scalability, cost, and reputation, businesses can make informed decisions and select a provider that aligns with their unique needs and objectives. Partnering with the right provider can streamline accounts payable processes, drive cost savings, and position your business for long-term success. https://katprotech.com/accounts-payable-and-purchase-order-automation/

Factors to Consider When Choosing Accounts Payable Services Providers.pptx

Katpro Technologies

Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024

How to convert PDF to text with Nanonets

naman860154

Tata AIG General Insurance Company - Insurer Innovation Award 2024

Explore 'The Codex of Business: Writing Software for Real-World Solutions,' a compelling SlideShare presentation that delves into digital transformation in healthcare. Discover through a detailed case study how Agile methodologies empower healthcare providers to develop, iterate, and refine digital solutions that address real-world challenges. Learn how strategic planning, user feedback, and continuous improvement drive success in deploying technologies that enhance patient care and operational efficiency. Ideal for healthcare professionals, IT specialists, and digital transformation advocates seeking actionable insights and practical examples of technology making a real difference.

The Codex of Business Writing Software for Real-World Solutions 2.pptx

Malak Abu Hammad

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A Domino Admins Adventures (Engage 2024)

Gabriella Davis

Finology Group – Insurtech Innovation Award 2024

Boost Fertility New Invention Ups Success Rates.pdf

sudhanshuwaghmare1

Axa Assurance Maroc - Insurer Innovation Award 2024