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
Selling your house in the financial crisis-stricken Greece is up to this day a great ordeal. When faced with such a challenge, I was baffled by the sparsity of conclusive data on land value at my birthplace city, Thessaloniki. Embarking on a personal mission and collecting and processing more than 10K online housing ads together with open data, I managed to render an insightful interactive visualization of the actual real estate values on borough and city block level that was published through the Greek media. Join me on this thought process journey to find out how to
o Gather vast online data with simple scripting
o Combine your data with open data into meaningful structures
o Create interactive data visualizations that have an actual impact @ infographeo.com
This will be an interactive session, so please feel free to bring your thoughts and questions to share during the session.
Data visualization requires data to be prepared before any meaningful analysis can be conducted. Finding insights, making correct observations and taking actions to drive outcomes therefore don't just depend on the way information is communicated but also on the preparation preceding the analysis.
In this webinar we discuss the key steps for data preparation to enable effective analysis and visual exploration of the data. We will show practical examples from projects we have worked on as well as share some simple data preparation ideas from our Makeover Monday challenges.
Lastly, we will show an example of how data preparation can enrich a dataset and enable further analysis.
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
It is easy to talk about the "Data Lake” as the answer to all data storage problems. However, not all Data Lakes are the same, and it is important to choose the right architecture for your data and use cases.
In this webinar, we will explore different Data Lake architectures - logical, storage, analytical etc. - from the point of view of the big data architect and user. We’ll understand the benefits of each, with examples drawn from the real-world experience of Hitachi Vantara in industries like manufacturing and finance.
Attendees will learn not only how to choose the model that works best for them, but will also come away with a sound understanding of the potential for analytics and intelligent applications built on their Data Lake architecture.
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 >
The Data Centre Maturity Model (DCMM) was created by The Green Grid and can help assess the current and desired states of your data centre(s), highlighting areas that could be enhanced using a maturity modeling approach.
*Please note: this webinar will be presented in Dutch.
Is Your Data Ready for GDPR?
As the deadline for GDPR approaches, it is time to get practical about protecting personal data.
We break down the steps for turning a data lake into a data hub with appropriate data management and governance activities: from capturing and reconciling personal data to providing for consent management, data anomyzation, and the rights of the data subject.
A smart approach to GDPR compliance lays a foundation for personalized and profitable customer and employee relations.
Watch, as experts from MAPR and Talend show you how to:
Diagnose the maturity of your GDPR compliance;
Set up milestones and priorities to reach compliance;
Create a foundation to manage personal data through a data lake;
Master compliance operations - from data inventory to data transfers to individual rights management.
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.
With new technologies such as Hive LLAP or Spark SQL, do you still need a data warehouse or can you just put everything in a data lake and report off of that? No! In the presentation, James will discuss why you still need a relational data warehouse and how to use a data lake and an RDBMS data warehouse to get the best of both worlds.
James will go into detail on the characteristics of a data lake and its benefits and why you still need data governance tasks in a data lake. He'll also discuss using Hadoop as the data lake, data virtualization, and the need for OLAP in a big data solution, and he will put it all together by showing common big data architectures.
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 >
Are you struggling to turn big data into useful, accurate, consistent, and impactful insights? Organizations are rapidly adopting new technologies like Hadoop, Spark, and Kafka to help lines of business develop new insights. However, with the sheer quantity of data available and complexity of new technologies, the opportunity to drive operational efficiencies and grow sales can feel overwhelming, inflexible, manual, and complex. Informatica's customers have successfully pursued digital transformation strategies through more systematic approaches for getting the right data, in the right place, at the right time to the right people.
In this webinar, learn how to:
• Design an architecture for data management with Hadoop and big data that can scale for large organizations
• Understand best practices for data integration, data quality, data cataloging, and data preparation
• Exploit automated approaches to data management to get more trusted data assets every time
Join experts from Cloudera and Informatica to learn about an enterprise approach to data management that enables big data to be turned into useful, accurate, consistent, and impactful business insights.
As more and more organizations delve into the world of big data, they’re noticing that it’s not wise to dump data into a data lake without proper guardrails in place. Instead, companies need to architect and build their data lake with scalability, flexibility and governance in mind.
Based on hundreds of data lake implementations, Zaloni has built a reference architecture that has proven to be scalable and future-proof. This architecture is based on a zone approach through which data can live and travel throughout its lifecycle. This zone-based approach can greatly facilitate data governance and management, particularly if a data lake management platform, such as the Zaloni Data Platform, is in place.
How should these zones be defined within a data lake environment? What should happen to data within each of these zones? In this webinar, Raj Nadipalli, Director of Product Support and Professional Services at Zaloni, will answer these questions and address how to architect a data lake that is future-proof in the ever-changing big data ecosystem.
As big data has exploded, the ability for companies to easily leverage it has imploded. Organizations are drowning in their own information, unable to see the forest through the trees, while the big players consistently outperform in their ability to deliver a great customer experience, faster, cheaper…As a result, the vast majority of companies are scrambling to catch up and become more agile, data-driven, to use their data more effectively so they can attract and retain their elusive customers...
Join 451 Research and Treasure Data to learn how to enable your line of business team to own their own data (instead of relying on IT) to be able to:
- deliver a single, persistent view of your customer based on behavior data
- make that data accessible to the right people at the right time
- Increase organizational effectiveness by (finally) breaking down silos with data
- enable powerful marketing tools to enhance the customer experience
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.