The enterprise data warehouse (EDW) has been at the cornerstone of enterprise data strategies for over 20 years. EDW systems have traditionally been built on relatively costly hardware infrastructures. But ever-growing data volume and increasingly complex processing have raised the cost of EDW software and hardware licenses while impacting the performance needed for analytic insights. Organizations can now use EDW offloading and optimization techniques to reduce costs of storing, processing and analyzing large volumes of data.
By simplifying the ability of companies to securely extract, orchestrate and act on data from when it is generated by energy assets to when it is transmitted to the cloud, Octave simplifies the development and commercialization of Energy IoT applications. With Octave, energy companies are empowered to realize the Energy IoT’s tremendous potential, with new demand response, energy efficiency optimization, predictive maintenance and other applications that maximize the value created by energy assets and minimize their environmental impact. In doing so, these Energy IoT applications can reduce energy costs, improve customer engagement, lower greenhouse gas emissions and increase energy reliability.
Start with Sierra to learn more about how our Octave D2C data orchestration solution can help you bring to market Energy IoT applications that reimagine the future of energy.
Published By: TeamQuest
Published Date: Sep 05, 2014
TeamQuest Director of Market Development Dave Wagner and Chris Lynn, Safeway's Capacity Manager and Performance Analyst, cover the application of automatic, exception-oriented analytics to a wide variety of IT and business metrics in order to simultaneously optimize service performance and IT cost. Multiple conceptual approaches are shared, including pros and cons. Most of the presentation includes real examples by which Safeway has integrated performance, capacity, business, and power data into an automated optimization process spanning 1000s of servers and virtual servers and their applications.
Big data has made quite an impression on organizations embarking on data journeys, hoping to glean valuable insights ranging from process optimization to customer-facing improvements. This research paper explores proven best practices that can help organizations overcome obstacles to deliver on big data potential.
Published By: MarkLogic
Published Date: Mar 29, 2018
Real World Evidence (RWE) requires the correlation of complex, frequently changing, unstructured data. To the enterprise architect, that means extracting value from data that doesn't neatly fit solutions. In this white paper, we dive into the details of why relational databases are ill-suited to handle the massive volumes of disparate, varied, and changing data that is required to be successful with RWE. It is for this reason that leading life science organizations are going beyond relational to embrace new kinds of databases. And when they do, the results can be dramatic.
Traditional brick-and-mortar multi-channel retailers have online competitors ruled by data scientists who define retail as a data mining and optimization problem. John Bible, Senior Director of Retail Data Science and Insight at Oracle Retail discusses the science of pricing, and predictions for the role of science in retail over the next five years.
In an era where Big Data decisions demand high-powered tools, organizations everywhere are still mired in complex spreadsheets that limit the speed and precision of their critical customer interactions.
Read this fact sheet to learn how you can evolve beyond what spreadsheets alone can achieve:
• Allow business users to easily create and compare “what if” scenarios, interact with compelling visualizations, and challenge, improve and build trust with stakeholders and collaborators
• Rapidly deploy new optimization features and applications practically at the speed of thought – without leaning on IT – while leveraging existing investments in other analytic tools (such as R, SAS, MATLAB, and even Excel)
Many organizations consider optimization only for their largest or most challenging business problems, often utilizing a small number of Operations Research professionals. But in our age of Big Data, market globalization and increased competition, many organizations are successfully making the case that optimization can be applied to a wider variety of business and operational decisions, and be developed by a new group of users — the organization’s business analysts.
With a proven track record of results demonstrating that organizations can increase profitability with business analysts applying optimization to many types of business problems, FICO’s proven development methodology is giving organizations the confidence to extend optimization practices across their enterprises.
Download this whitepaper to learn how Hortonworks Data Platform (HDP), built on Apache Hadoop, offers the ability to capture all structured and emerging types of data, keep it longer, and apply traditional and new analytic engines to drive business value, all in an economically feasible fashion. In particular, organizations are breathing new life into enterprise data warehouse (EDW)-centric data architectures by integrating HDP to take advantage of its capabilities and economics.
Most companies have a few people who are testers and optimizers by nature, interest, or experience. But what really moves the dial is when everyone in the company embraces a test-and-learn approach to improving the customer experience across all touchpoints.
Why is the test-and-learn approach so effective? When you test everything, your team values data over opinions. Everyone keeps learning — even from failures. The results? More visitors, more sales, happier customers, and a healthier bottom line.
To help you get there, this guide provides insights on:
What constitutes a culture of growth and optimization
Tips for building that culture in your own company
Lessons from marketing leaders who embrace the test-and-learn approach
Efforts to reduce capital and operating expenditures by consolidating data centers can fail if applications and network are not optimized. Learn about a consolidation strategy that goes beyond centralizing servers, routers, software, and switches to solve multiple business problems.
Read the white paper to learn:
- Strategies and best practice approaches to online testing
- Incremental steps to improving your online testing
- The benefits of different test types including A/B, A/Bn, multivariate, and multichannel
Want to solve rapid application development platform for building solutions across the entire lifecycle of manufacturing and supply chain business challenges? Optimizing supply chain strategies helps businesses readily account for massive amounts of data as well the myriad constraints and conflicting objectives within your business. This easy-to-modify solution incorporates strong and proven optimization engines, flexible workflow and usability at every level to drive consistent, transparent and profitable decisions, which ultimately drive the best action(s) for your business.
Increasingly, enterprises are opening their data and applications to partners, developers, mobile apps and cloud
services. APIs provide a standardized way to open up information assets across the web, mobile devices, serviceoriented
architecture (SOA) and the cloud. However, to make API information sharing safe, reliable and cost-effective,
enterprises must deal with critical security, performance management and data adaptation challenges.
CA API Management combines advanced functionality for back-end integration, mobile optimization, cloud
orchestration and developer management. It is unique in its ability to address the full breadth of enterprise
API management challenges.
Data centers are large, important investments that, when properly designed, built, and operated, are an integral part of the business strategy driving the success of any enterprise. Yet the central focus of organizations is often the acquisition and deployment of the IT architecture equipment and systems with little thought given to the structure and space in which it is to be housed, serviced, and maintained. This invariably leads to facility infrastructure problems such as thermal “hot spots”, lack of UPS (uninterruptible power supply) rack power, lack of redundancy, system overloading and other issues that threaten or prevent the realization of the return on the investment in the IT systems.
Data centers are large, important investments that when properly designed, built and operated, are an integral part of the business strategy driving the success of any enterprise, yet the central focus of organizations is often the acquisition and deployment of the IT architecture equipment and systems, with little thought given to the structure and space in which it is to be housed, serviced and maintained. This invariably leads to facility infrastructure problems, such as thermal hot spots, lack of UPS, rack power, lack of redundancy, system overloading and other issues that threaten or prevent the realization of the return on the investment in the IT systems.
Data centers are large, important investments that, when properly designed, built, and operated, are an integral part of the business strategy driving the success of any enterprise. Yet the central focus of organizations is often the acquisition and deployment of the IT architecture equipment and systems with little thought given to the structure and space in which it is to be housed, serviced, and maintained.
In this white paper Quest's data protection experts offer five tips for effective backup and recovery to help you avoid the challenges that might keep you from fully protecting your virtual assets and infrastructure.
ADCs are advanced load balancers with functions and features that enhance the performance of applications. Today, companies of all sizes with geographical dispersal of people and different data constructs require ADCs to optimize their complex application environments from web applications, to Exchange, SharePoint and databases. It is interesting that before the term ADC was used more recently (in the last decade), companies relied on load balancers for website availability and scalability. In this paper we will describe the fundamentals of a load balancing system and its evolution to an ADC.
Learn more about Watson (as seen on Jeopardy!), the latest IBM Research Grand Challenge, designed to further the science of natural language processing through advances in question and answer technology. This paper explains Watson's workload optimized system design and why this represents a new computing paradigm.
As media and channels proliferate with the upsurge in digital touchpoints, we have access to massive volumes of customer data. This leads to the personalization of customer interactions that drive customer strategy as a business strategy.
An effective marketing investment strategy will help you take inventory of your current measurement framework and develop a more accurate, reliable and consistent strategy for assessing and improving the performance of your marketing spend.