The Internet of Everything (IoE) is disrupting innovation models and causing market shifts. One of the most powerful IoE-driven opportunities will be the value created from big data and analytics. As IoE gains momentum and creates billions of new connections, each of those connections will be capable of producing data. The enterprises that can unlock the intelligence within that data — quickly and effectively — will hold the key to a powerful and sustainable competitive edge. Read More »
As they speed through the clouds, most air travelers are comfortable knowing that their pilot is not actually bothering to fly the plane. On the open highway, however, it may be harder to accept truck drivers who take their hands off the wheel to text, watch movies, or gaze at the scenery as it rolls lazily by.
Yet self-driving trucks could become a common sight in coming years. One company at the forefront of this technology is Daimler’s Mercedes-Benz brand. Recently, the company demonstrated its “Future Truck 2025” concept, with a modified vehicle that cruised down the autobahn at a top speed of 53 MPH. The driver was able to switch at will between manual control and the automated Highway Pilot system,.
I see the Highway Pilot as an exciting example of how the Internet of Everything (IoE) connects the unconnected. Using a convergence of innovations that leverage Wi-Fi, data analytics, radar, GPS, and stereo video sensors, Highway Pilot steers the truck, senses other vehicles, and maintains the most efficient speed and route. IN the process, it enables a whole new technology platform and business model. After all, many countries face a shortage of truck drivers; and fuel consumption issues and safety concerns persist — especially on long, grueling hauls.
I see the self-driving truck Read More »
In my recent blogs about building the right data strategy and analytics solutions, I discussed how Cisco is helping our customers to meet one of the toughest challenges brought on by the Internet of Everything (IoE) – cost-effectively managing massive amounts of distributed data. With solutions such as Cisco Data Virtualization and Cisco Big Data Warehouse Expansion (BDWE), our customers can bring all of this data together in ways that are meaningful to them. Utilizing the network to securely connect data throughout the IoE and providing advanced analytics, we help our customers predict outcomes so they can drive better decisions in real-time.
To keep up with growing demands for big data analytics, now is the time to look at workload automation end to end. In this blog, I would like to share the other aspect of big data analytics; building the right workload automation strategy to integrate data, analytics and operations.
In today’s big data analytics environments, IT staff is regularly managing increasingly complex processes that are co-dependent on one another and span applications and departments. Rather than implementing silos of automation, we are helping customers take advantage of workload automation from a unified perspective. Our enterprise-wide workload automation solution, Cisco Tidal Enterprise Scheduler (TES), simplifies end-to-end data management and automates diverse business processes across a broad set of applications, systems and environments.
For example, many business intelligence and analytics applications operate 24 hours a day. To handle a high volume of these jobs – many with service-level agreements – customers need the tools to receive and respond to alerts from anywhere. Using the Cisco Tidal Enterprise Scheduler client on their iPhones and iPads, our customers can receive alerts, check logs and remediate errors from anywhere. As organizations continue to require fast and timely business services, we put the power directly in the users’ hands. By using TES’ self-service portal, business users can monitor the progress of relevant workloads through a web browser and perform basic job control. In addition to reducing the downtime of a business user having to wait for IT to address their issue, this also takes some of the burden off IT.
TES is a key piece of any company’s big data and analytics software strategy and a priority for us at Cisco. Cisco IT uses TES internally and, due to successful deployment, is now encouraging further widespread internal adoption. Since Cisco TES is the first workload automation solution in the industry to have a suite of Hadoop adapters (as well as other data source and application adapters), Cisco IT is now additionally leveraging TES in Cisco’s own internal Big Data initiatives to deliver an end-to-end big data workload solution – as detailed here and here. We are continuously working to develop ways to integrate TES further with other Cisco Big Data solutions, such as the recently launched BDWE solution, to provide more value through holistic data management solutions.
Taking full advantage of big data delivers a tremendous competitive advantage to our customers. Cisco TES facilitates the end-to-end management of the entire process from data acquisition, to value extraction, to action. Stay tuned as we continue to deliver new capabilities to further bridge today’s gap between enterprise IT capabilities and business requirements.
To learn more about Cisco Tidal Enterprise Scheduler and the power of our integrated infrastructure for big data, check out our page.
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Can you feel the rumbling? Once firm ground now feels shaky. And that rushing sound you hear is the avalanche of data that threatens to bury businesses that aren’t prepared. Research firm IDC estimates that by 2020, the amount of digital information will explode to 40,000 Exabytes or 40 trillion GB (more than 5,200 GB for every man, woman, and child according to EMC). And while natural avalanches end quickly, it’s clear that the data avalanche is gaining momentum.
This data deluge has significant ramifications for companies and public sector organizations that are seeking answers to questions such as: How do you create insightful information from immense amounts of data? How much of your limited IT budget should you spend on Big Data solutions to protect your competitive position? What innovations are possible from new insights? How can these innovations transform your business? Read More »
We’ve reached the 8th installment of our blog series on Cisco’s Big Data and Analytics vision (beginning with Scott Ciccone’s blog on September 23). No doubt by now you have either seen or heard about Cisco’s broad data and analytics portfolio presented at Strataconf in New York on Oct. 15. And if you missed our October 21st executive webcast ‘Unlock Your Competitive Edge with Cisco Big Data and Analytics Solutions,’ please check it out. Now you’re probably eager to know how to make the most of our approach to data analytics. How can you benefit the most—and the most quickly—from data analysis in your organization?
Customers come to us to ask for support in extracting valuable and actionable business insights from their large stocks of network data. Their goal is always to drive both operational efficiencies and new revenue opportunities. Rapid changes in the business environment increase pressure on time-to-value: savings and revenues need to be brought in as quickly as possible. But traditional ways to extract value from data, complicated by volume, velocity and variety issues, often have a very long time-to-value. In fact, data analytics consulting projects historically take a year or longer to complete. Customers get handed large scale implementation plans and, by the time the program is implemented, the wind has changed: the market opportunity has closed, and the business has moved on.
That’s why for some time now I’ve been a student of accelerating time to value for data analytics. Our job is not just to show our customers the hidden business value of their data, but also to bring that value to them fast. We have developed a rapid prototyping, iterative approach that continuously develops actionable insights from network and other sources of data. Our approach contains four steps to help our customers quickly develop, test, and implement business ideas and processes:
Step One: We start by working with customers and identify key use cases through an “Internet of Everything” iterative planning approach. Our experts don’t just present an idea, but a complete, ready-to-test hypothesis, using visualization techniques and an analytics design approach to discover new ways to do business, based on analytics insights.
Step Two: We use a rapid data extraction approach to capture the data needed to test that hypothesis. We fully leverage Cisco’s Connected Analytics platform, enabling automated data collection and simple correlations exploration.
Step Three: Once we have the data we need, we apply a data science approach to build an “analytics sandbox” in which we test the proposed use cases and measure its outcomes. We use rapid prototyping to test theories, quickly working through iterations to develop a truly working business model for our customers’ unique situations. In the process we are able to identify new insights that became the basis for the next use cases.
Step Four: The result is a set of modular Business Insights, which we interpret and thoroughly test, and turn into an actionable plan that we execute. This makes it relatively easy for our experts to integrate insights and actions into our customers’ transformation initiatives—and in a fraction of the time of traditional data-driven solutions.
The world of top down, outside-in consulting, where value comes from individuals’ experience, is gone. Value today is enabled by the capability of companies like Cisco to extract and interpret data about our customers’ core business, enabling agile decision making and rapid process transformation.
As the Internet of Everything becomes a pervasive reality, we see that analytics is what creates value from all of these connections value. To learn more about Cisco’s vision for the Internet of Everything, read Joseph Bradley’s blog on Thursday, October 23! #UnlockBigData