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
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
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.
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.
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.
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.
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
No Code, Low Code Big Data Analytics from Simple Search to Complex Event Processing.
Logtrust is designed for fast data exploration and interaction with real-time visualizations on complex data streams and historical data at rest such as:
- Machine behavior during attacks
- Network traffic flow analytics
- Firewall events
- Application performance metrics
- Real-time threat hunting and cyber security
- IoT analytics
Explore Petabytes of data with Logtrust without worrying about storage costs or indexers, analyze billions of events per day with ultra-low latency queries, and experience unique real-time performance on trillions of events with over +150,000 ingest EPS per core, +1,000,000 search EPS per core, and +65,000 complex event processing EPS per core.
Live Data Exploration
Logtrust data is always fresh with real-time data updates in their native formats. Slice and dice subsets of data at any point in time for exploration and deep forensics on real-time data streams.
Powerful Data Exploration & Analytics
Accelerate time-to-insights and rich visualizations with simple point and click. Empower your team to quickly harness insights and make faster, smarter decisions. Optionally, use a single compact expressive SQL language (LINQ) and create reusable callable queries for more complex event processing operations.
Join this webinar to learn how to deploy a scalable and elastic architecture for Big Data analytics.
Hadoop and related technologies for Big Data analytics can deliver tremendous business value, and at a lower cost than traditional data management approaches. But early adopters have encountered challenges and learned lessons over the past few years.
In this webinar, we’ll discuss:
-The five worst practices in early Hadoop deployments and how to avoid them
-Best practices for the right architecture to meet the needs of the business
-The case study and Big Data journey for a large global financial services organization
-How to ensure highly scalable and elastic Big Data infrastructure
Discover the most common mistakes for Hadoop deployments – and learn how to deliver an elastic Big Data solution.
Watch this webinar to learn about Big-Data-as-a-Service from experts at Dell and BlueData.
Enterprises have been using both Big Data and Cloud Computing technologies for years. Until recently, the two have not been combined.
Now the agility and efficiency benefits of self-service elastic infrastructure are being extended to big data initiatives – whether on-premises or in the public cloud.
In this webinar, you’ll learn about:
- The benefits of Big-Data-as-a-Service – including agility, cost-savings, and separation of compute from storage
- Innovations that enable an on-demand cloud operating model for on-premises Hadoop and Spark deployments
- The use of container technology to deliver equivalent performance to bare-metal for Big Data workloads
- Tradeoffs, requirements, and key considerations for Big-Data-as-a-Service in the enterprise
Malgré quelques similarités, Hadoop et Spark sont souvent considérées comme la même technologie. Durant ce webcast, Marc Royer, Spécialiste SE et Big Data chez Dell EMC vous guidera à travers les différences entre ces outils, afin que vous puissiez choisir le bon pour votre projet Big Data.
Pendant ces 30 minutes vous découvrirez notamment :
- Pourquoi et comment les organisations se tournent vers le Big Data pour innover
- Spark et Hadoop, et les spécificités des deux outils
- Quelques cas d’usage de ces technologies
- Une méthodologie pour réussir votre projet Big Data et les bonnes questions à se poser pour choisir la technologie appropriée
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.
Join this webinar with Cisco and BlueData to learn how to deliver greater agility and flexibility for Big Data analytics with Big-Data-as-a-Service.
Your data scientists and developers want the latest Big Data tools for iterative prototyping and dev/test environments. Your IT teams need to keep up with the constant evolution of new tools including Hadoop, Spark, Kafka, and other frameworks.
The DevOps approach is helping to bridge this gap between other developers and IT teams. Can DevOps agility and automation be applied to Big Data?
In this webinar, we'll discuss:
- A way to extend the benefits of DevOps to Big Data, using Docker containers to provide Big-Data-as-a-Service.
-How data scientists and developers can spin up instant self-service clusters for Hadoop, Spark, and other Big Data tools.
-The need for next-generation, composable infrastructure to deliver Big-Data-as-a-Service in an on-premises deployment.
-How BlueData and Cisco UCS can help accelerate time-to-deployment and bring DevOps agility to your Big Data initiative.
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
The biggest challenges that organizations face are to determine how to obtain value from big data, and how to decide where to start. Many organizations get stuck at the pilot stage because they don't tie the technology to business processes or concrete use cases.” (Gartner, 9/14)
This session will provide insight into how to build a roadmap and project charter for a big data solution. A solution that is both ready to address your first use case while serving as a platform for your future big data needs. A must for anyone looking to find out how to accelerate strategic initiatives and journey to big data maturity.
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.
Join this webinar with EMC and BlueData for a discussion on cost-effective, high-performance Hadoop infrastructure for Big Data analytics.
When Hadoop was first introduced to the market 10 years ago, it was designed to work on dedicated servers with direct-attached storage for optimal performance. This was sufficient at the time, but enterprises today need a modern architecture that is easier to manage as your deployment grows.
Find out how you can use shared infrastructure for Hadoop – and separate compute and storage – without impacting performance for data-driven applications. This approach can accelerate your deployment and reduce costs, while laying the foundation for a broader data lake strategy.
Get insights and best practices for your Big Data deployment:
- Learn why data locality for Hadoop is no longer relevant – we’ll debunk this myth.
- Discover how to gain the benefits of shared storage for Hadoop, such as data protection and security.
- Find out how you can eliminate data duplication and run Hadoop analytics without moving your data.
- Get started quickly and easily, leveraging virtualization and container technology to simplify your Hadoop infrastructure.
And more. Don't miss this informative webinar with Big Data experts.
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.