Today's enterprises need broader access to data for a wider array of use cases to derive more value from data and get to business insights faster. However, it is critical that companies also ensure the proper controls are in place to safeguard data privacy and comply with regulatory requirements.
What does this look like? What are best practices to create a modern, scalable data infrastructure that can support this business challenge?
Zaloni partnered with industry-leading insurance company AIG to implement a data lake to tackle this very problem successfully. During this webcast, AIG's VP of Global Data Platforms, Carlos Matos, and Zaloni CEO, Ben Sharma will share insights from their real-world experience and discuss:
- Best practices for architecture, technology, data management and governance to enable centralized data services
- How to address lineage, data quality and privacy and security, and data lifecycle management
- Strategies for developing an enterprise-wide data lake service for advanced analytics that can bridge the gaps between different lines of business, financial systems and drive shared data insights across the organization
This is the age of data science. We have more data, computing power and software packages than ever before, and we’re driving real value with data science. But challenges remain: fragmented and dirty data, collaboration issues, and long project cycle times.
Keys to success: a ‘data-first’ approach, enabling collaboration, and a focus on prediction. Cloudera Data Science delivers the unified platform you need for rapid time to value with the most advanced machine learning techniques, including deep learning.
Do you need to combine data from multiple sources to get business insights? Do you know if the data you rely on is always accurate and up-to-date? Do you want to have insights quicker to meet business needs? Do you rather spend time on strategic tasks than maintaining the data warehouse?
Crunchbase also experienced these pain points. With over 31 million visitors to their website each year, Crunchbase collects and uses an incredible amount of data, and therefore needs a powerful analytics platform to aggregate all the data to ask the right questions. Since deploying Periscope Data Warehouse, Crunchbase was able to take their analytics to the next level by allowing them to leverage all their data — from their marketing stack to Salesforce to website impression data — and to build a comprehensive view of their business and customers.
Join Ryan Seagar, Head of Sales Engineering of Periscope Data, as he presents a live 30-minute demo and the Crunchbase case study on how Periscope Data Warehouse enables data teams streamline their entire analytics workflow — from data ingestion to analysis and reporting, offloading the mundane maintenance tasks while still maintaining full control and visibility .
Do you know what your top ten 'happy' customers look like? Would you like to find ten more just like them? Come learn how to leverage 1st & 3rd party data to map your customer journey and drive users down a path where every interaction is personalized, fun, & data-driven. No more detractors, power your Customer Experience with data!
In this webinar you will learn:
-When, why, and how to leverage 1st, 2nd, and 3rd party data
-Tips & Tricks for marketers to become more data driven when launching their campaigns
-Why all marketers needs a 360 degree customer view
Paul Bruton discusses the move to a holistic approach to next gen data management. Looking at digital transformation strategies, he explains how Hitachi Vantara’s object storage can address common challenges - from cloud complexity to data governance and compliance - with its advanced custom metadata architecture to make data more intelligent.Read more >
Jason Hardy speaks about the evolution of the Hitachi Content Platform. Focusing on the latest addition to the portfolio, Hitachi Content Intelligence (HCI), he explains how it delivers a superior enterprise search experience. Learn how HCI can process and discover information from multiple data streams and find meaningful correlations between that data to enable data-driven decision-making.Read more >
How do you make sure your data is bit correct in the source and target systems? In this video, learn how the Big Data Compare feature in HVR enables you to make sure your data is correct and in sync.
VP of Field Engineering, Joe deBuzna, explains how the Big Data Compare function works in HVR, why it is important for your business, and how it can identify and mitigate errors.
When it comes to Big Data Analytics, do you know if you are on the right track to succeed in 2017?
Is Hadoop where you should place your bet? Is Big Data in the Cloud a viable choice? Can you leverage your traditional Big Data investment, and dip your toe in modern Data Lakes too? How are peer and competitor enterprises thinking about BI on Big Data?
Come learn 5 traps to avoid and 5 best practices to adopt, that leading enterprises use for their Big Data strategy that drive real, measurable business value.
In this session you’ll hear from Hal Lavender, Chief Architetect of Cognizant Technologies, Thomas Dinsmore, Big Data Analytics expert and author of ‘Disruptive Analytics: Charting Your Strategy for Next-Generation Business Analytics, along with Josh Klahr, VP of Product, as they share real world approaches and achievements from innovative enterprises across the globe.
Join this session to learn…
- Why leading enterprises are choosing Cloud for Big Data in 2017
- What 75% of enterprises plan to drive value out of their Big Data
- How you can deliver business user access along with security and governance controls
Everyone is searching for meaning in their data, but you need to determine the truth firstRead more >
All enterprise data systems need foundational master data contentRead more >
The idea of the data lake was alluring; the means to having data at your fingertips, filtered, profiled, secure and business-ready for data consumers to rapidly derive higher-levels of business value. However, this widely adopted concept didn’t come with an instruction manual.
The past few years have been turbulent times for enterprise data and analytics. In this live discussion, the presenters look beyond the lake, discussing the combination of self-service data preparation and data management and governance as one; a truly functional data marketplace or “data bazaar”. In addition, they will touch on other key enablers fueling the adoption of the self-service marketplace, including;
•Data as a service,
•Smart data ingestion – validation/profiling,
•Smart data cataloging/search,
Today, big data is enabling the advanced analytics that companies have dreamed of for driving their business. And as forward-thinking companies take advantage of big data and advanced analytics to drive digital transformation initiatives, it is forcing the laggards to realize that they will have to do the same if they want to survive.
The generally accepted architectural model for harnessing big data is a data lake. But data lakes, if leveraged simply as cheap storage within which to dump data, will inevitably disappoint. As the saying goes, garbage in, garbage out. Data lakes present unique challenges that must be dealt with if that big data set is going to be turned into actionable information.
So what does it take to succeed with a data lake? Why do some organizations get real value out of big data, while others struggle?
In this webinar, Matt Aslett, Research Director of Data Platform and Analytics at 451 Research and Kelly Schupp, VP of Data-driven Marketing at Zaloni, will discuss ideal data lake use cases such as Customer 360 and IoT. They will also discuss Zaloni’s data lake maturity model with which the data-eager company can chart its ideal course and roadmap.
The Geisinger Health Plan cares for over 500,000 members in Northeast and Central Pennsylvania. During this webinar, you’ll learn how the Geisinger team is using Informatica’s metadata driven products and solutions to ensure that data is reliable and trusted. You’ll discover both strategic and tactical considerations for leveraging data quality to meet your goals, including industry best practices, design concepts for governance organizations and the development of core technical competencies. Don’t miss this webinar where you’ll hear about lessons learned and innovative approaches directly from the experts at Geisinger.Read more >
Trusted customer data is the difference maker between happy customers and getting blasted on social media. By using our contact data verification tools, you can quickly clean your customer contact data so that it can be relied upon for success. Whether the end goal is improved customer relationships or another data-driven digital transformation objective, clean contact data enables you to engage with your customers more effectively.
During this webinar, you’ll hear from Salema Rice, Chief Data Officer of Allegis Group, on how great customer data has improved her customers' experience. You’ll discover the positive effects right from a CDO and learn about how you can get started in creating better customer outcomes.
It is the insights from big data that can be so illuminating. They show the new services that can differentiate your business. They enable you to create the customer-centric organisation by understanding what consumers expect.
From supply chains to business processes, you will have the visibility to improve efficiency, while saving money and cutting risk. The potential result? The right products and services, delivered at the right time – extending your reach to new markets and opportunities.
Learn about the advantages that come with bringing your data onto one platform in this on-demand webinar, and get a glimpse into Periscope Data’s vision for a unified data platform.Read more >
In this webinar, Vinaya Thummala and Sarah Moen will share insights on the data governance program at American Family Insurance. They will discuss the value of high quality data to their program and what it has meant to their success. By leveraging Informatica Data Quality, they have been able to ensure that their data is reliable, consistent, and clean. In this webinar, you will:
•Hear an overview of the Information Quality Management Program at American Family Insurance
•Lean how data governance activities are supported by data quality policies, standards and processes to continuously monitor and improve the reliability of business data
•Understand the effective use of data quality in projects: check and ensure the quality of all data, including existing data, transformed data and newly created data
•Discover their Data Quality as a Service Model: Data quality services deployment at Enterprise level for technical expertise, shared infrastructure, and different engagement models to meet all business needs
When it comes to choosing data storage solutions outside of your primary application, a maze of options exists out there, but how do you choose which type is right for your needs? Should you go for a data lake, or a data warehouse? And which methodology should you apply?
Register for our upcoming webinar, “Choosing the right Enterprise Data Architectures for your business”, where we will discuss:
The motivation for replicating operational data into various “stores”, as well as the implications;
A high-level overview of the various options available, including data warehouses, data vaults, data hubs, data marts and data lakes;
Commonly used practices for building these architectures;
Advantages and disadvantages of different practices and methodologies.
Finally, the webinar will end end with the way in which CloverETL can help you along the way.
Big Data Analytics success has been constrained by the difficulty in accessing siloed data and by the traditional IT approach of gathering requirements, designing and building extracts to turn data into valuable data assets. As IT organizations are backlogged with servicing business requests, business analysts and data scientists are looking for alternative methods to discover relevant data, share data with colleagues across divisions or geographies and prepare data assets for actionable insights.
In this deep dive, you will have the opportunity to learn about new features of Informatica Big Data Management 10.1 and Informatica’s latest innovation, Intelligent Data Lake, leveraging self-service efficiency for business analysts and data scientists by incorporating semantic search, data discovery and data preparation for interactive analysis while governing data assets.
The newest buzzword after Big Data is AI. From Google search to Facebook messenger bots, AI is also everywhere.
Machine learning has gone mainstream. Organizations are trying to build competitive advantage with AI and Big Data.
But, what does it take to build Machine Learning applications? Beyond the unicorn data scientists and PhDs, how do you build on your big data architecture and apply Machine Learning to what you do?
This talk will discuss technical options to implement machine learning on big data architectures and how to move forward.
The use of an emerging data fabric, offers enterprises a number of benefits and advantages including the ability to break through the gravitational pull of legacy data architectures and capture the full potential of all your data.
This webinar will detail how the deployment of a data fabric can enable enterprises to more quickly and easily scale across data volumes, data types and locations. The session will also provide an overview on how a data fabric reduces storage costs and increases application agility and reliability – with the underpinning to support the successful pursuit of:
* IoT through a data fabric’s capability of handling data flows from the edge to the cloud, centralizing learning, and distributing intelligence back to the edge for real-time responsiveness.
* Machine Learning/AI with the fabric able to handle the complex data flows and logistics to support the rapid deployment and coordination across machine learning models, algorithms and analytic tools
* Microservices and containers with the underlying data fabric able to support intelligent streams and support the mobility and flexibility for elastic stateful applications and analytic processes relying on shared data.
Bi-directional data movement need not be feared when using HVR for real-time data integration. In this video, Glenn Goodrich, Director of Enablement, explains how bi-directional data movement can be accomplished efficiently, accurately, and in real-time with HVR.
Chapter 1: What is Bi-Directional? 1:13
Chapter 2-1: How to Implement Bi-Directional 3:32
Chapter 2-2: Bi-Directional Considerations 5:03
Chapter 3: Why Implement Bi-Directional? 11:46
Additional Areas of Interest:
DDL Operations and Truncates: 7:15
Loop Avoidance: 8:15
Conflict Detection Resolution (CDR): 10:06
Your mission-critical datacenter runs on a highly resilient infrastructure: it has N+1, N+2 or better still, 2N mechanical and electrical capacity redundancy for critical components. But does it really? Based on Panoptic’s experience many datacenters carry a variety of lurking issues that might develop into a cascading failure. According to the Uptime Institute, the vast majority of even the world’s most elite datacenters do not operate as designed/installed on day one. This webinar will cover, in case study form, some of the causes underlying poor performance, and how a proactive maintenance program can uncover and help avoid an impact on the availability of services.Read more >
EU: General Data Protection Regulation (GDPR)
The clock is ticking and it’s time to act as Europe’s most demanding and far reaching Data Security regulation to date has been published. This webinar from Informatica’s Data Security Team will examine the key requirements of GDPR, and look at how we can use new Data Intelligence capabilities to be in control of our sensitive data assets.
During the Webinar there will be a demonstration of Informatica’s Secure@Source technology that swept the board at the recent Info Security awards, specifically to demonstrate how it’s now possible within a single view to find, and track all the GDPR qualifying data across the organisation, to see who’s using it and what security controls are in place to protect it. This ability to visualise the movement and control of sensitive data will be the critical key to an effective GDPR strategy. This is not a regulation that anyone can afford to ignore, and for those who get it wrong the compensation and regulatory fines could be on a par with the current cost of PPI to the banks ! Join us and get ahead of the game.