Data is growing at amazing rates and will continue this rapid rate of growth. New techniques in data processing and analytics including AI, machine and deep learning allow specially designed applications to not only analyze data but learn from the analysis and make predictions.
Computer systems consisting of multi-core CPUs or GPUs using parallel processing and extremely fast networks are required to process the data. However, legacy storage solutions are based on architectures that are decades old, un-scalable and not well suited for the massive concurrency required by machine learning. Legacy storage is becoming a bottleneck in processing big data and a new storage technology is needed to meet data analytics performance needs.
Businesses are overwhelmed with data; it’s a blessing and a curse. A curse because it can overwhelm traditional approaches to storing and processing it. A blessing because the data promises business insight that never existed earlier. The industry has spawned a new term, “big data,” to describe it. Now, IT itself is overwhelmed with its own big data. In the press to roll out new services and technologies—mobility, cloud, virtualization—applications, networks, and physical and virtual servers grow in a sprawl. With them comes an unprecedented volume of data such as logs, events, and flows. It takes too much time and resources to sift through it, so most of it lies unexplored and unexploited. Yet like business data, it contains insight that can help us solve problems, make decisions, and plan for the future.
Published By: Teradata
Published Date: Jan 30, 2015
This report is about two of those architectures: Apache™ Hadoop® YARN and Teradata® Aster® Seamless Network Analytical Processing (SNAP) Framework™. In the report, each architecture is described; the use of each in a business problem is illustrated; and the results are compared.
Published By: Teradata
Published Date: Jan 30, 2015
It is hard for data and IT architects to understand what workloads should move, how to coordinate data movement and processing between systems, and how to integrate those systems to provide a broader and more flexible data platform. To better understand these topics, it is helpful to first understand what Hadoop and data warehouses were designed for and what uses were not originally intended as part of the design.
Download this white paper to learn how a well-architected workload automation solution can help you:
• Shrink application development time and cost
• Deliver higher quality digital services
• Increase IT’s agility to meet the demands of the business"
"In the paper, “Integrate Big Data into Your Business Processes and Enterprise Systems” you’ll learn how to drive maximum value with an enterprise approach to Big Data. Topics discussed include:
• How to ensure that your Big Data projects will drive clearly defined business value
• The operational challenges each Big Data initiative must address
• The importance of using an enterprise approach for Hadoop batch processing
This paper, "Workload Automation – From Application Development to Digital Service Delivery," describes how a workload automation solution can eliminate the manual processes developers now use to define batch workflows and communicate them to schedulers.By extending the use of workload automation to developers, organizations can implement applications faster, slash costs, and increase service quality.
A step-change in the pace of business today brings enterprise resource planning (ERP) systems face-to-face with the largest transformation in their role since they were first introduced in the early 1990s. The rise of a new generation of business automation demands real-time information processing and visibility on a scale that was unthinkable just a few years ago. Coupled with—and in large part enabled by—this new wave of business automation, there has been a surge in the pace of business itself. Learn how Real-Time ERP puts you and your business at the forefront of this change.
Get practical advice from IT professionals on how to successfully deploy all-flash arrays for Oracle, SAP and SQL Server workloads in a SAN environment. You'll explore topics such as transaction processing speed, storage management, future requirements planning, workload migration and more.
Mainframes continue to provide high business value by combining efficient transaction processing with high-volume access to critical enterprise data. Business organizations are linking mobile devices to mainframe processing and data to support digital applications and drive business transformation. In this rapidly growing scenario, the importance of providing excellent end-user experience becomes critical for business success.This analyst announcement note covers how CA Technologies is addressing the need for providing high availability and a fast response time by optimizing mainframe performance with new machine learning and analytics capabilities.
Published By: Lucidworks
Published Date: Dec 14, 2016
Download this whitepaper to learn about the benefits and trade-offs of contextual and data-based analysis. Recommendations and answers are provided by the next generation of enterprise applications that use search-based features and capabilities to improve performance and add value.
Big data has raised the bar for data virtualization products. To keep pace, TIBCO® Data Virtualization added a massively parallel processing engine that supports big-data scale workloads. Read this whitepaper to learn how it works.
Published By: Trifacta
Published Date: Feb 12, 2019
Over the past few years, the evolution of technology for storing, processing and analyzing data has been absolutely staggering. Businesses now have the ability to work with data at a scale and speed that many of us would have never thought was possible. Yet, why are so many organizations still struggling to drive meaningful ROI from their data investments? The answer starts with people. In this latest Data Science Central webinar, guest speakers Forrester Principal Analyst Michele Goetz and Trifacta Director of Product Marketing Will Davis focus on the roles and responsibilities required for today’s modern dataops teams to be successful. They touch on how new data platforms and applications have fundamentally changed the traditional makeup of data/analytics organizations and how companies need to update the structure of their teams to keep up with the accelerate pace of modern business. Watch this recorded webcast to learn: What are the foundational roles within a modern dataops team a
Published By: Trifacta
Published Date: Feb 12, 2019
Over the past few years, the evolution of technology for storing, processing and analyzing data has been absolutely staggering. Businesses now have the ability to work with data at a scale and speed that many of us would have never thought was possible. Yet, why are so many organizations still struggling to drive meaningful ROI from their data investments? The answer starts with people.
In this webinar, guest speakers Forrester Principal Analyst Michele Goetz and Trifacta Director of Product Marketing Will Davis focus on the roles and responsibilities required for today’s modern dataops teams to be successful. They touch on how new data platforms and applications have fundamentally changed the traditional makeup of data/analytics organizations and how companies need to update the structure of their teams to keep up with the accelerate pace of modern business.
Watch this recorded webcast to learn:
What are the foundational roles within a modern dataops team and how to align skill set
US based leading multinational mass media conglomerate had high volume of actionable tickets open for resolution and other related challenges for which LTI helped in building an event correlation system to find out the Root Cause Analysis of multiple events and analyse number of tickets. This was achieved by leveraging Mosaic Decision platform for processing. Download complete case study.
This white paper discusses the concept of shared data scale-out clusters, as well as how they deliver continuous availability and why they are important for delivering scalable transaction processing support.
The confluence of AI and Industry 4.0 is transforming image processing. As image vision becomes widespread, there is an increasing need to transition stand-alone imaging to an integrated driver of automation feeding insights back into the business systems that monitor overall factory performance.
Download the whitepaper to learn more about fitting multiple demands into a single platform—
• Building an industrial system with advanced functions like machine vision and Industry 4.0 connectivity
• Minimizing the footprint of the systems to save space, cost and power consumption
• Adhering to principles of long life, safety, reliability, real-time control functionality alongside AI and IIOT capabilities
Keeping the lights on in a manufacturing environment remains top priority for industrial companies. All too often, factories are in a reactive mode, relying on manual inspections that risk downtime because they don’t usually reveal actionable problem data.
Find out how the Nexcom Predictive Diagnostic Maintenance (PDM) system enables uninterrupted production during outages by monitoring each unit in the Diesel Uninterrupted Power Supplies (DUPS) system noninvasively.
• Using vibration analysis, the system can detect 85% of power supply problems before they do damage or cause failure
• Information processing for machine diagnostics is done at the edge, providing real-time alerts on potential issues with ample of lead time for managers to rectify
• Graphic user interface offers visual representation and analysis of historical and trending data that is easily consumable
In a perfect world, every sales order your company receives would go straight into your SAP system. But in reality, orders sent by fax and email end up as paper that gets pushed around the office. And those are the ones that cost the most to process.
Automation is widely used in the business world. Still, the concept of order processing automation remains a bit of an enigma - even among those who already know a thing or two about it. That's why it's critical to give yourself a refresher before driving the project forward and getting stakeholders on board.
This eBook highlights the six key stakeholders in order management that need to be challenged to go beyond the status quo. Automation aligns with their priorities - it's your job to deliver that message. Download this eBook now to learn more about the key roles in an order processing automation project.
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