By George Trujillo, principal data strategist, DataStax; and Ara Bederjikian, president, Titanium Intelligent Solutions - The IoT industry is evolving to support a wide range of use cases and operating models. Titanium's broad SaaS platform was built to tackle the array of IoT challenges that business and IT leaders face.
By Sam Ramji, Chief Strategy Officer, DataStax - Is giving people the right to change, alter, and amend your software a good thing? What about doing this for your data? Companies used to think that publicizing their source code was the same as giving away their secret sauce.
By David Andrzejek, head of financial services, DataStax - Schrodinger's Cat is a quantum mechanics thought experiment in which a hypothetical cat can be considered to be both alive and dead simultaneously. I can't help but think of open banking in the United States — it's not here, and, at the same time, it's very much here.
By Thomas Been - Winning enterprises take data, process it, and use it to deliver in-the-moment experiences to customers. Starbucks, Netflix, The Home Depot, and countless other organizations large and small have built great success based on this understanding. But what does that success look like, and what are the challenges faced by organizations that use real-time data?
By Chet Kapoor, Chairman & CEO of Datastax - I have the great privilege of getting to know leaders from the world's most recognized brands and fastest-growing startups. We share the stories, obstacles, and defining moments that have helped shape our careers. Each individual’s journey is unique, but there’s a common thread connecting all of these leaders: no one’s path to success has been a straight line. Most of our journeys look more like a zigzag – or maybe even a jungle gym.
By Chet Kapoor, Chairman and CEO, DataStax - There is no doubt that this decade will see more data produced than ever before. But what’s truly going to transform our lives, define the trajectory of each of our organizations, and reshape industries is not the massive volume of data. It’s the unmatched degree to which this data can now be activated in applications that drive action in real time: minute by minute (or even second by second), across work, play, and commerce. Where technology might have been a constraint in the past, it’s now an enabler.
By Aaron Ploetz, Developer Advocate - It’s not only the whims and expectations of consumers that drive the need for real-time or near real-time responsiveness. Think of a bank’s requirement to detect and flag suspicious activity in the fleeting moments before real financial damage can happen. Or an e-tailer providing locally relevant product promotions to drive sales in a store. Real-time data is what makes all of this possible.
By Ed Anuff, Chief Product Officer, DataStax - Enterprises across industries have been obsessed with real-time analytics for some time. The technology that powers this toolset that aims to make critical business decisions quickly is expected to amount to a $50.1 billion market by 2026.
By George Trujillo, Principal Data Strategist, DataStax - Any enterprise data management strategy has to begin with addressing the 800-pound gorilla in the corner: the “innovation gap” that exists between IT and business teams. It’s a common occurrence in all types of enterprises, and it’s difficult to wrestle to the ground. IT teams grapple with an ever-increasing volume, velocity, and variety of data, which pours in from sources like apps and IoT devices. At the same time, business teams can’t access, understand, trust, and work with the data that matters most to them. This scarcity of quality data might feel akin to dying of thirst in the middle of the ocean.
David Andrzejek, Head of Financial Services, DataStax - While the widespread and large-scale use of data has been well-known among internet giants, the effective capture and use of data has now become a key competitive weapon for enterprises in all segments of the economy. Data and analytics are now driving more than 20% of revenue at almost one in five companies. While enterprises in all sectors of the economy will compete with data, the effective capture and use of data in information-intensive sectors like online services, banking, and financial services is especially critical and will separate winners from losers.
By Chet Kapoor, Chairman and CEO, DataStax - Customers demand experiences that meet them at the speed of life. Think about an app that lets you know exactly when your latte will be ready or one that offers you alternate flight options as soon as you miss your connection.
By David Andrzejek, head of Financial Services, DataStax - Capital One might be the sixth-largest bank in the United States, but it's working hard to harness its data and the cloud to execute much more like a fintech. The company is on a mission to revolutionize the banking industry through technology and data and serves as a model for harnessing the power of data for growth.
By Reed Peterson, Field CTO, Telecom, DataStax - It’s one thing to deliver performance and new services that impress customers, but doing so at the scale of one of the largest wireless carriers in the world and at the speed required to compete in a cutthroat industry requires data – petabytes of it. As well as a clear understanding of how to take full advantage of it in real-time.
By George Trujillo, Principal Data Strategist, DataStax - Web3 is now firmly established as the technology ecosystem that lets developers build decentralized applications. But its reliance on blockchain technology has also raised concerns about its ecological impact.
By George Trujillo, Principal Data Strategist, DataStax - Think about your favorite recipe. You might have all the ingredients for an apple pie, but there’s no guarantee all the elements will come together to produce a delicious dessert. Similarly, many organizations have built data architectures to remain competitive, but have instead ended up with a complex web of disparate systems which may be slowing them down.
By Chet Kapoor, Chairman and CEO, DataStax - Think about an organization where, at each moment, a recommendation engine is talking to every part of the business – sharing immediate data on live sales and inventory, the purchasing pipeline, and all the context that impacts the business (market conditions, supply chain issues, even weather). This is nirvana. Enterprises that rely on processing data in batches and depend on analysts to review dashboards cannot deliver data-driven actions when it matters most – and they will be left behind.n
By George Trujillo, Principal Data Strategist, DataStax - If, as Gartner puts it, an operating model brings the broader business model to life, then execution patterns are an important part of breathing life into an operating model. Patterns maintain consistency when executing on the operating model. Mike Tyson is often quoted as saying, “Everyone has a plan until they get punched in the mouth.”
By Cori Land, Corporate Strategist, DataStax - Data creates the context for decision-making. As you approach data saturation, your decisions become more likely to win. If you have anything less than data saturation, your decisions are made with more uncertainty than need be. That could be acceptable if the risk of getting it wrong is acceptable. But if precision matters, you’ll need more context. There are two dimensions to data saturation: breadth and depth of coverage.
By Ed Anuff, Chief Product Officer, DataStax - When it comes to digital transformation, data architectures have gotten short shrift. Many enterprises have focused on modernizing by moving applications to the cloud, or building ecommerce offerings (if they are retailers). But in many cases, data has been left out of the digital transformation story because data systems tend to be large, monolithic, fragile, and difficult to deal with—in other words, there are significant risks to the business if the modernization process doesn’t go as planned.
By Thomas Been, Chief Marketing Officer, DataStax - The concept of real-time data has been around for a while. “Reactive apps” were promoted in the early 2000s as the next big thing that would drive customized experiences for customers and increase enterprise competitiveness. Back then, it was a great vision--but it was just that, a vision.