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
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.
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.
Watch this online session and learn how to reconcile the changing analytic needs of your business with the explosive pressures of modern big data.
Leading enterprises are taking a "BI with Big Data" approach, architecting data lakes to act as analytics data warehouses. In this session Scott Gidley, Head of Product at Zaloni is joined by Josh Klahr, Head of Product at AtScale. They share proven insights and action plans on how to define the ideal architecture for BI on Big Data.
In this webinar you will learn how to
- Make data consumption-ready and take advantage of a schema-on-read approach
- Leverage data warehouse and ETL investments and skillsets for BI on Big Data
- Deliver rapid-fire access to data in Hadoop, with governance and control
In financial services, the top big data analytics use cases include customer analytics to understand customer journey using data from all customer interaction channels, predict and avoid customer churn, and fraud and compliance. The financial and corporate benefits of these use cases range from improving customer retention, to hundreds of millions of dollars in incremental revenue and protection of shareholder value.
In this webinar, learn from big data analytics experts:
- Top 3 use cases in financial services
- The importance of applying the appropriate technologies
- The data driven insights that will give companies a competitive edge
Hadoop is not just for play anymore. Companies that are turning petabytes into profit have realized that Big Data Management is the foundation for successful Big Data projects.
Informatica Big Data Management delivers the industry’s first and most comprehensive solution to natively ingest, integrate, clean, govern, and secure big data workloads in Hadoop.
In this webinar you’ll learn through in depth product demos about new features that help you increase productivity, scale and optimize performance, and manage metadata such as:
• Dynamic Mappings – enables mass ingestion & agile data integration with mapping templates, parameters and rules
• Smarter Execution Optimization – higher performance with pushdown to DB, auto-partitioning and runtime job execution optimization
• Blaze – high performance execution engine on YARN for complex batch processing
• Live Data Map – Universal metadata catalog for users to easily search and discover data properties, patterns, domain, lineage and relationships
Register today for this deep dive and demo.
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.
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
Implementing Hadoop can be complex, costly, and time-consuming. It can take months to get up and running, and each new user group typically requires their own infrastructure.
This webinar will explain how to tame the complexity of on-premises Big Data infrastructure. Tony Baer, Big Data analyst at Ovum, and BlueData will provide an in-depth look at Hadoop multi-tenancy and other key challenges.
Join us to learn:
- The pitfalls to avoid when deploying Big Data infrastructure
- Real-world examples of multi-tenant Hadoop implementations
- How to achieve the simplicity and agility of Hadoop-as-a-Service – but on-premises
Gain insights and best practices for your Big Data deployment. Find out why data locality is no longer required for Hadoop; discover the benefits of scaling compute and storage independently. And more.
Data is collected in IoT solutions for a purpose - it is transformed into information which is subsequently used to produce actionable insights.
The three primary types of IoT data, in order of volume, are:
- Time based (time series, time interval), e.g. power, voltage, current, temperature and humidity
- Geospatial, e.g. person/device location
- Asset specific data
These types of data have special characteristics that need to be catered to. Join this webinar with Cloud Technology Partners Joey Jablonski, VP of Big Data & Analytics and Ken Carroll, VP of IoT, as they discuss some important aspects of how such data can be ingested, modeled, stored and used in IoT solutions.
Get your questions answered and hear how the Spin-Merge benefits our abilities to deliver advanced analytics and machine learning for your Big Data needs.
Join two of our HPE Software Big Data leaders to hear firsthand about the recently announced spin-merge. Gain direct insight into what it means for you. This is a big opportunity for us to deliver even more of the advanced analytics at Exabyte scale that all data driven organizations depend on in our fast moving world. Hear about our Big Data portfolio strategy including upcoming innovations addressing performance at scale for tomorrow’s workloads, infrastructure independent deployments and a growing set of in database machine learning algorithms. Bring your questions and join us on this accelerated journey to success.
La digitalisation du marketing et l’émergence de nouvelles applications génèrent un flux toujours plus important de données, de toutes formes et tailles. L’exploitation de ces informations permet de mieux cibler, acquérir et satisfaire la clientèle, cependant, trop peu de directions marketing parviennent à en tirer parti.
Le 13 décembre à 11 heures, participez à notre webinaire Intelligent Data Lake et découvrez grâce à des exemples concrets de mise en œuvre comment :
- Visualiser le parcours client global pour identifier les programmes les plus efficaces et optimiser le mix marketing ;
- Développer des stratégies efficaces pour mieux cibler et acquérir de nouveaux clients ;
- Tirer profit des données issues du Big Data à travers tous les points de contact pour créer de la valeur métier.
Informatica Intelligent Data Lake
La solution Intelligent Data Lake d’Informatica offre la data préparation en libre-service, en combinant l’automatisation, l’intégration et la gestion de la qualité des données, aux capacités de gestion de la gouvernance et de la sécurité requises pour tirer la véritable valeur métier de tous types de données, tout en rationalisant les risques.
The German Cancer Research Center (DKFZ) uses self-service big data analytics to radically improve the genomic research process. Their new insights have allowed them to identify better treatment plans for cancer patients.
During this one-hour on-demand webinar, Dr. Fritz Schinkel, head of Fujitsu’s Big Data Competence Center and a Fujitsu Distinguished Engineer, discusses how the combined Datameer and Fujitsu platform helps the DKFZ:
--Perform deeper analysis on raw datasets representing millions of genomic positions without requiring data reduction techniques that can compromise results
--Dramatically reduce the time it takes to analyze raw genomic datasets for each patient to speed creating patient treatments
Discover the newly launched features in Qubole, powered by Data Intelligence, that automates mundane Data Model performance appraisal and simplifies Data Ops. This session will provide a detailed walkthrough of Qubole’s latest offering in Data Intelligence that includes Data Model insights and Recommendations including Partitioning, Formatting, and Sorting that helps optimize data models for improved performance and computing resources. In addition, learn about Qubole’s latest offering in self-service analytics and how it can improve analysts productivity by making data discovery easy through column and table name auto-suggestion and completion, and insights preview.Read more >
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.
Join Matt Aslett of 451 Research for a briefing on the current big data analytics trends that are driving customers to utilize fast big data applications for increased customer engagement, reduced risk, and greater operational efficiency. After which, Nathan Trueblood will share DataTorrent's direct experiences working with enterprise organizations who are deploying fast big data apps to accelerate business outcomes TODAY and why they believe their customers' use of these applications will be the difference between success or failure in the future.Read more >
We have come a long way since the term "Big Data" swept the business world off its feet as the next frontier for innovation, competition and productivity. Hadoop, NoSQL and Spark have become members of the enterprise IT landscape, data lakes have evolved as a real strategy and migration to the cloud has accelerated across service and deployment models.
On the road ahead, the demand for real-time analytics will continue to skyrocket alongside growth in IoT, machine learning, and cognitive applications. Meeting the speed and scalability requirements of these types of workloads requires more flexible and efficient data management processes – both on-premises and in the cloud. Flexible deployment and integration options will become a must-have for projects.
Finally, the need for data governance and security is intensifying as businesses adopt new approaches to expand their data storage and access via data lakes and self-service analytics programs. As data, along with its sources and users, continues to proliferate, so do the risks and responsibilities of ensuring its quality and protection.
Join us to watch the replay of "What's Ahead in Big Data and Analytics" to get real direction and practical advice on the challenges and opportunities to tackle in 2018.