By processing real-time data from machine sensors using artificial intelligence and machine learning, it’s possible to predict critical events and take preventive action to avoid problems. TIBCO helps manufacturers around the world predict issues with greater accuracy, reduce downtime, increase quality, and improve yield.
Read about our top data science best practices for becoming a smart manufacturer.
The Internet of Things (IoT) didn’t just connect everything everywhere; It laid the groundwork for the next industrial revolution.
Connected devices sending data was only one achievement of the IoT—but one that helped solve the problem of data spread across countless silos that was not collected because it was too voluminous and/or too expensive to analyze.
Now, with advances in cloud computing and analytics, cheaper and more scalable factory solutions are available. This, in combination with the cost and size of sensors continuously being reduced, supplies the other achievement: the possibility for every organization to digitally transform.
Using a Smart Factory system, all relevant data is aggregated, analyzed, and acted upon. Sensors, devices, people, and processes are part of a connected ecosystem providing:
• Reduced downtime
• Minimized surplus and defects • Deep insights
• End-to-end real-time visibility
“Vestas is a global market leader in manufacturing and servicing wind turbines,” explains Sven Jesper Knudsen, Ph.D., senior data scientist. “Turbines provide a lot of data, and we analyze that data, adapt to changing needs, and work to create a best-in-class wind energy solution that provides the lowest cost of energy.
“To stay ahead, we have created huge stacks of technologies—massive amounts of data storage and technologies to transform data with analytics. That comes at a cost. It requires maintenance and highly skilled personnel, and we simply couldn’t keep up. The market had matured, and to stay ahead we needed a new platform.
“If we couldn’t deliver on time, we would let users and the whole business down, and start to lose a lot of money on service. For example, if we couldn’t deliver a risk report on time, decisions would be made without actually understanding the risk landscape.
Integration is the lifeblood of today’s digital economy, and middleware is the software layer connecting
different applications, services, devices, data sources, and business entities. This Ovum Decision
Matrix (ODM) is a comprehensive evaluation to help enterprise IT leaders, including chief information
officers (CIOs), enterprise/integration architects, integration competency center (ICC)/integration
center of excellence (CoE) directors, and digital transformation leaders select a middleware-as-aservice
(MWaaS) suite best suited to their specific hybrid integration requirements.
Since it first started providing air passenger services in 2000, JetBlue has been
innovating. It was the first airline to embrace dot.com transactions and electronic
ticketing, and continues to churn out industry-leading inventions as described
here. When business needs changed in 2014, JetBlue embarked on very robust
digital transformation based on TIBCO integration and analytics technology—and
the company was recognized with the first-ever TIBCO Trailblazer Impact award
for the incredible effect this project was having on its strategic differentiation. In
this case study, Director of Shared Development Services Andi Azzolina describes
the objectives, initiatives, capabilities, and achievements making up JetBlue’s
journey towards becoming the most caring travel provider in the world.
With data the new competitive battleground, businesses that take advantage of
their data will be the leaders; those that do not will fall behind.
But gaining an advantage is a more difficult technical challenge than ever because
your business requirements are ever-changing, your analytic workloads are
exploding, and your data is now widely-distributed across on-premises, big data,
the Internet of Things, and the Cloud.
TIBCO® Data Virtualization is data virtualization software that lets you integrate
data at big data scale with breakthrough speed and cost effectiveness. With
TIBCO Data Virtualization, you can build and manage virtualized views / data
services that access, transform, and deliver the data your business requires to
accelerate revenue, reduce costs, lessen risk, improve compliance, and more.
The popularity of integration platform as a service (iPaaS) started with business users looking to gain control and share data among their proliferating SaaS apps?without needing IT intervention.
iPaaS was then adopted by IT to support business users to ensure security measures were being maintained and to provide more of a self-service environment. Now, iPaaS has evolved from a niche solution to taking a much bigger role:
Read this whitepaper to learn about:
Drivers for cloud integration
Five emerging uses cases for iPaaS that enable better responsiveness, APIs, event-driven capabilities, human workflows, and data analysis
Questions to ask when evaluating your current solution
The use of SaaS applications within an organization is the new normal. In fact, there's a good chance that just your marketing department alone is using over 10 SaaS products.
According to Gartner, the 2015 worldwide market for SaaS software application sales was $33.4 billion, with projections to double to $67.2 billion by 2019. Integration needs are changing, with SaaS applications, as well as mobile traffic, social networks, IoT, suppliers, partners, and customer channels all new integration points that will need to be captured in your business processes.
Read “Five Principles for Integrating Software as a Service Applications” to learn:
Key principles for successful hybrid integrations
New integration use cases to grow your business upward and outward
The why and how of integration as both an enabler and a differentiator
Benefits of the TIBCO integration platform and its various offerings
Maintaining a competitive edge today means building a Digital Enterprise capable of taking full advantage of social, mobile, web, cloud, “things,” (sensors and devices), and analytics technologies. Among the terms used to describe this business transition is “the API Economy,” an economy in which APIs are no longer just an IT concern, but the underpinnings of new revenue streams and new business models that are disrupting entire industries.
Read this paper to learn about:
New, modern applications being built for the enterprise
Application ecosystems and extending the value of your company in the API Economy
Two ways to integrate devices in the Internet of Things
The microservices approach to application development
The role of API management in the digital enterprise
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.
Whilst businesses of all kinds are utilizing data analytics, many are still only using it to make simple changes that lead to a set of rigid processes. Whereas the more customer-focused organizations are realizing that to deliver exceptional experiences, they need to be able to react to customer data in real-time and predict what might happen next. And that means going beyond simple analytics.
Read our whitepaper to discover what analyst firm Forrester has identified as the Enterprise Insight Platform, technology designed to enable companies to transform into truly data-driven businesses.
With data and analytics the new competitive battleground, businesses that take advantage will be the leaders; those that do not will fall behind. But with data so distributed, gaining this advantage is a huge challenge. Unless you have data virtualization, a better, faster way to meet your analytic data needs. Read this white paper to learn who needs data virtualization and what kinds of benefits others have achieved.
Despite being knowledgeable about their industry and experienced in running their organizations, the majority of business users lack expertise in analytics and visualization techniques—but that doesn't stop them from wanting to have a go. But making tools easier and more widely accessible is only part of the answer. A better approach is to work both sides of the gap. To make tools that can empower business users to discover and unlock value in their data—and that extend capabilities for experts, so they can share the analytics workload, improve efficiency, and focus on higher level work.
There are so many opportunities for businesses to collect data that getting a clear picture of all of it can be an uphill battle—and leveraging it for insight can be nearly impossible. But whether you are a start-up or a multinational conglomerate, not taking advantage of the available data is a mistake you cannot risk making. According to a 2016 McKinsey & Company study, over the past three years, digital leaders have achieved revenue growth five times greater, an operating margin profit eight times greater, and a return to shareholder value two times higher than laggards.
Companies today need a closed loop system that combines data, insight, and action. Download this paper to learn about the goals of a system of insight (SOI), the common set of technologies that all systems of insight need, and how an SOI can make a difference in your business.
Are you considering data virtualization for your organization today? In this paper you will learn 10 core truths about data virtualization and gain essential knowledge for overcoming analytic data bottlenecks and driving better outcomes.
TIBCO Spotfire is the premier data discovery and analytics platform, which provides powerful capabilities for our customers, such as dimension-free data exploration through interactive visualizations, and data mashup to quickly combine disparate data to gain insights masked by data silos or aggregations.
According to Forrester Research, "Enterprise data virtualization has become critical to every organization in overcoming growing data challenges," with faster access to connected data, self-service, and agility among the many benefits seen.
In this report, Forrester analyzes past research and Forrester Wave reports, user need assessments, and vendor and expert interviews to evaluate the offerings of top vendors in enterprise data virtualization. In compiling the vendor rankings, the report reviews the current offering, strategy, and market presence for the 13 most significant vendors.
They discuss where TIBCO ranks in the evaluation and positions TIBCO Data Virtualization as a leader in enterprise data virtualization
Read The Forrester Wave™: Enterprise Data Virtualization, Q4 2017 report to learn more.
Expanding analytic capabilities are critical to digitizing the business, optimizing costs, accelerating innovation, and surviving digital disruption
Historically, manufacturers were almost solely focused on reducing costs by applying automation and analytics to engineering, R&D, manufacturing operations, and quality organizations. Even though the strategies used within these areas are still needed, they are not sufficient to ensure business survival and continuity in the age of Industry 4.0 and the IoT.
Today, it is paramount that smart manufacturers broaden their scope because disruptive innovations in data acquisition, storage, and analytics technology have enabled an entirely new degree of automation and virtualization, promising a complete 360-degree high-fidelity virtual data-driven integrated views of all operations—from suppliers and supply chains, through equipment, processes, and manufacturing practices, to final product testing and customer satisfaction.
Download this paper
Produced in collaboration with INFOPRO Digital with participation from Capgemini
MAINTENANCE MADE EASY WITH THE HELP OF DATA
Predictive maintenance involves gathering targeted data for analysis, the results of which will help anticipate potential failures before they occur. Companies opt for this type of maintenance to avoid predictable incidents and repair equipment, assembly lines, or machinery with minimum impact on their operations.
World leader in design and manufacture of innovative sensing solutions that enhance safety, security, and energy efficiency.
For this manufacturers of high-tech imaging systems, monitoring accuracy and product quality are critical. Any quality problem could mean a part fails sooner than expected, or triggers a false alarm at a customer site that causes unnecessary panic.
By setting up automated manufacturing analytic workflows with the TIBCO StatisticaTM platform, the company can complete complicated processes in just a few minutes and improve product quality by decreasing the variability of everything they produce.
TIBCO Spotfire® Data Science is an enterprise big data analytics platform that can help your organization become a digital leader. The collaborative user-interface allows data scientists, data engineers, and business users to work together on data science projects. These cross-functional teams can build machine learning workflows in an intuitive web interface with a minimum of code, while still leveraging the power of big data platforms.
Spotfire Data Science provides a complete array of tools (from visual workflows to Python notebooks) for the data scientist to work with data of any magnitude, and it connects natively to most sources of data, including Apache™ Hadoop®, Spark®, Hive®, and relational databases. While providing security and governance, the advanced analytic platform allows the analytics team to share and deploy predictive analytics and machine learning insights with the rest of the organization, white providing security and governance, driving action for the business.
Ask the average business user what they know about Business Intelligence (BI)
and data analytics, and most will claim to understand the concepts. Few, however,
will profess to know how analytics works or to have the skills needed to put it
into practice. Despite being knowledgeable about their industry and experienced
in running their organizations, the majority of business users lack expertise in
analytics and visualization techniques—but that doesn’t stop them from wanting
to have a go.
This situation has led to ease of use and accessibility becoming the main focus
for recent updates from all the leading BI vendors—but making tools easier and
more widely accessible is only part of the answer.
A better approach is to work both sides of the gap. To make tools that can
empower business users to discover and unlock value in their data—and that
extend capabilities for experts, so they can share the analytics workload, improve
efficiency, and focus on higher level work.
The use of SaaS applications within an organization is the new normal. There is
a good chance that just your marketing department is using more than 10 SaaS
products, which is reflected in the amount you are spending on SaaS. According
to Gartner, the 2015 worldwide market for SaaS software application sales was
$33.4 billion, with projections to double that to $67.2 billion by 2019.1 Clearly,
your integration needs are changing. SaaS applications, as well as mobile
traffic, social networks, IoT, suppliers, partners, and customer channels are new
integration points that will need to be captured in your business processes.
This paper presents five principles for successful hybrid integrations.
Integration is the lifeblood of today’s digital economy, and middleware is the software layer connecting different applications, services, devices, data sources, and business entities. This Ovum Decision
Matrix (ODM) is a comprehensive evaluation to help enterprise IT leaders, including chief information officers (CIOs), enterprise/integration architects, integration competency center (ICC)/integration center of excellence (CoE) directors, and digital transformation leaders select a middleware-as-aservice (MWaaS) suite best suited to their specific hybrid integration requirements.
Download this whitepaper to read further on Hybrid integration suites for cloud service, API-led, B2B, and mobile application integration.