Why Data Science is Critical to Your Business

Amidst the barrage of industry buzzwords and fleeting trends, the core foundation of most organizations—data strategy—often does not make the headlines. Yet, this vital function is where the real story unfolds. If you are reading this, you might wonder, "Why hasn't data strategy been part of all the hype or news cycle recently?” Let me be candid: I have been in the trenches. I have worked with data for supply chain, enterprise resources, manufacturing, with data-at-rest, with data-in-motion, as an ethical hacker, and in solving data visualization challenges. I have led data transformations that scaled mountains and faced the abyss of our own data disasters.

But here is the thing - I have learned what is at stake and how to minimize disasters. And that is invaluable.

Data is not merely numbers or files; it is the lifeblood of your business. Yet, mishandling it can lead to nightmares. Data protection is not just about avoiding fines or preserving your brand image; it is about keeping your company's heartbeat steady. I have sat in those agonizing meetings with teams facing the grim reality of lost data. It is an experience that etches the weight of data responsibility deep into one's soul.

Automation gone wrong is not just about wasted resources—it can derail entire business strategies. I have witnessed automation projects run off the rails, yielding nothing. But from those failures, I learned to spot the pitfalls in the project lifecycle, to understand the nuances, and to respect the fine balance between human and machine. Now, when I talk automation, it is not from a theoretical standpoint but from a place of well-earned scars and celebrated triumphs.

Change Management that ignores the human factor in change can send shockwaves through an organization. I have seen firsthand the turmoil, the unspoken frustrations, and the quiet departures that occur when change is mismanaged. Raw data does not capture the apprehension of a team facing change or the morale impact when a transition goes awry. But I have been there, leading the charge, feeling the resistance, and eventually guiding teams to the light at the end of the tunnel.

Process Mining is not just a technical task—it is a pulse check for your business's operations. If you misread it, the consequences can be catastrophic. I recall when a misalignment in process mining painted a rosy picture, while the company was on the brink of a collapse. But from the ashes of those missteps, I have built a toolkit of wisdom that ensures we are not just skimming the surface, but diving deep, understanding core issues, and engineering sustainable solutions.

I am not here to give you textbook answers. There is a world of difference between reading about a storm and weathering one. In the landscape of data strategy, I have experienced a wide range of situations. So, when I share advice, know it has been forged in the fires of real-world challenges. Every piece of advice and  strategy I suggest is backed by experience, both good and bad.

There is a saying in our industry: "Trust but verify." Well, I am laying my experiences on the table, the good, the bad, and the downright ugly. That is what real-world experience looks like. And that is why, when I talk about data strategy, you should listen.

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Back in the day, our tech marvel was a calculator that could remember a whole 10 numbers. Fast forward to now, and we're immersed in a world where Artificial Intelligence (AI) doesn't just crunch numbers but chats, creates, and even attempts humor (though some AI jokes still need a bit of fine-tuning).

I've been navigating the tech landscape for over two decades, witnessing the apprehension that often shadows new innovations. It's essential to strike a balance between healthy skepticism and the exaggerated fears some narratives push. Are we really safe from the hidden dangers of AI? Remember the Y2K panic? We half-expected our kitchen appliances to rebel! Yet, through every wave of concern, there's always been a brighter side, and AI is a testament to that.

Healthcare Revolution: AI is reshaping healthcare. From predicting patient deterioration to aiding intricate surgeries, AI is at the forefront of medical advancements. Having seen tech evolve from pagers to smartphones, I'm eager to witness the next AI-driven health innovations.

Environmental Conservation: Gone are the days when solar panels were our green tech's crowning glory. AI is now spearheading efforts to optimize renewable energy and forecast environmental shifts, safeguarding our planet for the coming generations.

Enhanced Creativity: There's a myth that AI might overshadow human creativity. Yet, my experience shows AI as a tool that enhances our artistic pursuits, from music to visual arts.

Efficient Problem Solving: In earlier times, our go-to tech fix was a good old thump. Now, AI analytics can proactively address issues before they become headaches.

While there are genuine concerns about AI's broader implications, our adaptability shines through. We've embraced and molded the internet, mobile tech, and social platforms to our advantage, and AI will be no different. Challenges? We see them as opportunities in disguise.

Amidst the apprehension, it's vital to recognize the unparalleled advantages AI offers. And if you're ever anxious about AI's dominance, here's a fun fact: they still haven't mastered the art of a killer joke!

Merriam Webster’s Dictionary defines “convergence” as the merging of distinct technologies, industries or devices into a unified whole.

With over 23,000 active patents, Cisco has a rich heritage of unifying technologies to deliver new value to customers and partners. In 2009, for instance, Cisco converged siloed storage devices and protocols into the fabric of a Unified Computing System, reducing cost and improving scale. Today, Cisco continues to bridge technical islands and create innovative solutions.

Observability: Cisco’s new digital convergence frontier

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Observability is one of the strategic pillars that define Cisco’s solution strategy and enables the delivery of quality digital experiences anywhere, every time. Last year, adding to Cisco’s all-in bet on observability, Cisco CFO Scott Herren told the investment community to measure Cisco on a new category, “Application Experience.” Cisco’s last three acquisitions, Epsagon, Replex and Opsani, added resources and features to the observability platform.

At Cisco Live, the annual technology conference in June 2022, Liz Centoni, EVP, Chief Strategy Officer & GM, Applications, unveiled to over 25,000 attendees the new cloud native observability capabilities through AppDynamics Cloud for its full-stack observability solution. She boldly stated that Cisco is all in on observability, with a vision for a standard operating model that views the entire technology stack regardless of location or scale.

AppDynamics Cloud was designed to meet cloud native environment scaling needs and complement existing AppDynamics application performance monitoring. With deep insight into the user experience, full-stack observability is a solution that adds value across the entire business with real-time insights that benefit brand loyalty and revenue.

Cisco’s full-stack observability builds a bridge for Cisco partners and customers from observing the technology to visibility into the businesses’ health. For any business transaction or application the solution sees, it can tag and create real-time dashboards. From revenue waiting in a shopping cart to the number of trades pending to the number of mortgages waiting to be underwritten to oil moving through a pipeline to the number of players in a gaming experience, whatever a business cares about, if information is in the application, full-stack observability can correlate the technology performance within the context of the business result.

Observability across-the-stacks

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Cisco continues to make advancements to achieve its vision for a unified operating model with integrations in every major architecture. With devices across enterprise networking, collaboration, data center and security intelligently reporting in, Cisco can provide insights through in-depth performance analysis on issues like real-time security threats and traffic latency across the entire application stack.

Full-stack observability combines network, compute, storage, security, cloud and application insights and adds business context. Full-stack observability is the new frontier for high-value partner practices and technologists that can elevate and translate beyond the “this server is broken” to “here is what is impacting the business in this way.” Already, some full-stack observability customers see a 40% reduction in severity 1 issues, with some boasting 90%.

This convergence creates new capabilities where the health of technology is viewed in business context. For example, if there is a delay in trading, it impacts revenue. If there is a slow server in a gaming experience, it causes users to switch games. If there is a mobile application delivering a poor experience on a specific page or interaction because of a confusing interface, the abandoned page or interaction may be identified. These are tangible and measurable business impacts. Full-stack observability allows customers and partners to observe beyond the technology performance to offer insights into business performance, pinpointing issues in real-time.

Today, most network, security, infrastructure, storage, application, cloud and business operations teams are generally siloed with separate niche tools that often don’t easily share information. Now, Cisco and its rich ecosystem of partners are all in on delivering the next era of convergence full-stack observability makes possible.