The Buried Treasure of Enterprises
Capitalizing on the Unknown Knowledge with AI
The former president of Hewlett Packard, Lew Platt, once said:
“If HP knew what HP knows, we’d be three times more productive.”
– Lew Platt
While Lew Platt said this over 30 years ago, it could not be more relevant today. The quote captures the untapped potential lying dormant within organizations around the world. In the last decade, the exponential growth of data has led to a treasure trove of insights and knowledge hidden in the depths of corporate databases and data warehouses. Yet for most companies, this big data remains an underutilized asset.
Imagine if an organization could suddenly access and operationalize all the collective knowledge distributed across its people, processes, and systems. The productivity and innovation unlocked would be transformative.
The challenge is that harnessing big data has traditionally been extremely difficult. Technical obstacles around storing, processing, and analyzing vast volumes of data, combined with issues of data quality, talent shortages and prohibitive costs, have left most big data initiatives falling short of their potential.
Today, the rapid technological advancements of artificial intelligence and machine learning is enabling powerful new approaches to deriving insights from big data. AI is finally at a stage where it can automate discovery, handle unstructured data, power predictive analytics, and make insights accessible to business users across the organization.
Leading this revolution are innovative companies like Palantir, which is empowering organizations to transform their vast data repositories into operational intelligence. By effectively leveraging AI and big data, Palantir’s platforms are enabling the proverbial “three times more productive” that Lew Platt envisioned 30 years ago. In the following, we will dive deeper into the big data opportunity and explore how Palantir and other pioneers are harnessing the power of AI to finally deliver on the promise of big data.
The Big Data Opportunity
The world is experiencing an unprecedented explosion of data. Over the past decade, the amount of data generated and collected by organizations has grown exponentially. By 2025, global data creation is projected to reach more than 180 zettabytes – up from just 2 zettabytes in 2010.
Yet for most companies, the vast majority of this data remains untapped and underutilized. It sits in siloed databases and data warehouses, with valuable insights and knowledge hidden within its depths. According to Forrester, up to 73% of all data within an enterprise goes unused for analytics.
This represents an immense missed opportunity. When effectively leveraged, big data has the power to transform nearly every aspect of an organization. It can enable faster, smarter decision-making, uncover cost savings, improve customer engagement, optimize operations and much more. Studies show that data-driven organizations are more productive and profitable than their peers.
Challenges of Harnessing Big Data
Harnessing the power of big data is no easy feat. Organizations face a long list of technical challenges when attempting to store, process and analyze the massive volumes of data they collect. Legacy systems strain under the weight of petabytes and exabytes, while the computational power required to crunch through it all can be immense.
But the challenges don't stop there. Even if you can wrangle your data into a usable format, issues around quality, accessibility, and security can make it difficult to extract real value. Inconsistent formats, missing fields, and siloed data sources can lead to a garbage-in, garbage-out scenario that undermines trust in data-driven insights.
Adding to these technical hurdles is a critical shortage of data science talent. The specialized skills required to work with big data are in high demand but short supply, leading to intense competition and sky-high salaries for qualified professionals. At the same time, the cost, and complexity of big data infrastructure can be prohibitive, causing many initiatives to stall or fail to get off the ground.
It's a perfect storm of challenges that has left many organizations struggling to capitalize on their big data assets. But advances in artificial intelligence are starting to change the game, making it possible to overcome these obstacles and unleash the full potential of big data.
The AI Revolution in Big Data Analytics
Just as organizations were drowning in the challenges of big data, breakthroughs in artificial intelligence and machine learning have thrown them a lifeline. These technologies are revolutionizing big data analytics, enabling powerful new approaches that were once the subject of science fiction.
One of the biggest game-changers is AI's ability to automate insights discovery. Rather than relying on armies of data scientists to manually sift through data looking for patterns and correlations, AI algorithms can do it automatically and at lightning speed. They can spot hidden trends, detect anomalies, and surface valuable insights that human analysts might miss.
AI is also a master at handling unstructured data—the free-form text, images, audio, and video that make up an estimated 80% of all data generated today. Traditional analytics tools struggle with this type of data, but AI can process and analyze it with ease, extracting valuable insights that were previously locked away.
Perhaps most exciting is the potential for AI-powered predictive analytics. By learning from historical data, AI models can make eerily accurate predictions about future events and outcomes. This can help organizations anticipate customer needs, forecast demand, optimize pricing and much more.
But the benefits of AI-powered analytics aren't just for data scientists and technical experts. The real power comes from making these insights accessible to business users across the organization. With intuitive interfaces and natural language querying, AI analytics tools can put the power of big data in the hands of salespeople, marketers, HR professionals and beyond.
Palantir: Turning Big Data into Operational Intelligence
Enter Palantir, the mysterious tech giant that's quietly revolutionizing how organizations harness their data. Founded in 2003 by a group of PayPal alumni and Stanford computer scientists, Palantir has built a reputation as the go-to firm for turning vast amounts of data into actionable intelligence.
At its core, Palantir is a data integration and analytics powerhouse. Its platforms, Gotham and Foundry, allow organizations to integrate massive volumes of data from disparate sources into a single, unified data asset. But that's just the beginning.
What sets Palantir apart is its ability to layer on advanced analytics and operational tools that enable real-time decision-making and action. Gotham, designed for government agencies, excels at uncovering hidden patterns and connections in complex data. It's been used to track down terrorists, combat insider trading, and even locate missing children.
Foundry, meanwhile, brings the power of Palantir to the commercial world. It's a full-stack data platform that combines data integration, analytics, and operational applications in one place. With Foundry, businesses can optimize supply chains, detect fraud, improve customer engagement and more.
The results speak for themselves. Palantir's software has been credited with everything from helping the US military track down Osama bin Laden to enabling Airbus to save millions through supply chain optimization. Merck used Foundry to speed up drug research during the pandemic, while one of the world's largest hedge funds used it to manage risk and improve trading decisions.
What's impressive is how Palantir makes the power of big data accessible to non-technical users. Its intuitive interfaces and pre-built applications allow business users to ask complex questions and get answers in real-time, without needing to know SQL or Python.
In essence, Palantir is turning big data from a liability into an asset. By making it possible to integrate, analyze and operationalize data at scale, Palantir is helping organizations across industries make better decisions, automate processes, and create millions in economic value. And they're just getting started.
As Palantir expands its reach beyond governments and into the commercial world, its potential to transform industries is immense. But they're not without competition.
The Competitive Landscape
While Palantir may be the most enigmatic player in the big data arena, they're far from the only one. The competitive landscape is fierce, with tech giants and startups alike vying for a piece of the ever-growing big data pie.
One of the key contenders is Databricks, the company behind the popular Apache Spark analytics engine. Databricks' Unified Data Analytics Platform combines data engineering, science, and business analytics, allowing organizations to process massive amounts of data and extract insights all in one place. Their focus on open source and interoperability has won them fans, with customers like Shell, HSBC, and 3M singing their praises.
Snowflake is another company to keep an eye on, with their cloud-native data warehouse that can handle both structured and semi-structured data. Snowflake's secret sauce is its ability to decouple storage and compute, allowing for near-infinite scalability and flexibility. They've been growing with high-profile customers like Capital One, Adobe, and Sony Pictures.
In the self-service analytics space, Alteryx is a standout. Their platform allows business users to prep, blend, and analyze data without writing code, making sophisticated insights accessible to the masses. Alteryx has a loyal following among data analysts and business intelligence pros, with customers like Audi, McDonald's, and Unilever.
But you can't talk about big data without mentioning the cloud computing behemoths—Amazon, Microsoft, and IBM. Amazon Web Services offers a smorgasbord of big data services, from data warehousing with Redshift to real-time analytics with Kinesis. Microsoft's Azure Synapse Analytics combines data warehousing and big data analytics, while their Power BI platform is a leader in data visualization. IBM, meanwhile, is betting big on AI with Watson Studio for data science and machine learning.
So how does Palantir stack up against these competitors? In some ways, it's an apples-to-oranges comparison. Palantir's focus on complex, mission-critical applications sets them apart, as does their track record with government agencies. They also offer a more vertically integrated stack, with tools for data integration, analytics, and operations all in one place.
But Palantir's competitors have advantages of their own. Databricks and Snowflake, for example, are more open and interoperable, making it easier to fit them into an existing data stack. And the cloud giants offer a level of scale and infrastructure that's hard to match.
Ultimately, the big data landscape is evolving at breakneck speed, with new players and innovations emerging all the time. Databricks' $1 billion funding round and Snowflake's IPO are just two examples of the massive momentum in this space. As organizations race to harness their data and extract insights, the competition among these players will only intensify. And that's good news for enterprises, who stand to benefit from the relentless pace of innovation.
Aleph Alpha: Foundational AI for Big Data
Amid the crowded field of big data players, a new unknown contender is emerging from an unlikely place: Heidelberg, Germany. Aleph Alpha, a rising star in the European AI landscape, is making waves with its focus on developing advanced language models and AI tools specifically for enterprise and government applications. Aleph Alpha has secured a $500 million investment from a consortium of industry heavyweights, including Bosch, Schwarz Group (Lidl, Kaufland), and SAP – companies that desperately need to put their hidden data to productive use.
What sets Aleph Alpha apart is its mission to make AI accessible and applicable for real-world use cases. Rather than chasing consumer hype and developing large language models just for the sake of it, they're laser-focused on empowering businesses and public sector organizations with AI capabilities. Their flagship product, the Luminous language model, has already demonstrated impressive feats like fact-checking its own outputs — a critical feature for enterprise decision-making.
The investor lineup is a testament to Aleph Alpha's potential. Bosch is already working on "BoschGPT" to streamline internal data discovery and automate code documentation. SAP is integrating Aleph Alpha's tech into its business process optimization suite. And Schwarz Group plans to deploy it across everything from product descriptions to customer service.
But Aleph Alpha's ambitions go beyond just commercial success. They're positioning themselves as a champion for European AI innovation and digital sovereignty. By partnering with the likes of Ipai, a massive AI research center backed by the Dieter Schwarz Foundation, they're aiming to build a homegrown AI ecosystem that can compete with Silicon Valley giants.
Of course, challenges remain. Aleph Alpha's language model still lags behind OpenAI's GPT in many areas–let alone Palantir. And as a European player, they may struggle to match the scale and resources of their American and Chinese rivals. But with an all-star cast of industrial partners, Aleph Alpha is well-positioned to at least help them make known what is currently unknown.
Becoming “Three Times More Productive”
The big data revolution is just getting started. As we hurtle towards 2025 and beyond, the sheer volume of data generated and collected is set to explode. But it's not just about the quantity of data. The real game-changer is how AI-powered analytics will transform this digital deluge into a goldmine of insights and innovation. Gartner forecasts that by 2025, 75% of enterprises will shift from piloting to operationalizing AI, driving a 5x increase in streaming data and analytics infrastructures.
Real-time analytics will become the new normal, enabling businesses to make split-second decisions based on up-to-the-millisecond insights. AI-driven automation will also kick into high gear, with intelligent algorithms and machine learning models doing the heavy lifting of data processing and analysis.
For organizations that effectively harness their big data, the opportunities are immense. Those that can turn their data into a strategic asset will gain a massive competitive edge, leaving their data-blind rivals in the dust. The race is on to see who can become a true data-driven enterprise. And in this high-stakes contest, the spoils will go to the swift, the smart, and the AI-savvy.
In the end, it all comes back to Lew Platt's prophetic words: "If only HP knew what HP knows, we would be three times more productive." AI is the key that will finally unlock the full power and potential of big data. By harnessing the vast troves of data scattered across their organizations, businesses can tap into a wellspring of hidden knowledge and insight.
For investors, the smart money is on companies that provide the picks and shovels of this new gold rush – the big data analytics tools and AI platforms that will help businesses strike it rich. From Palantir to Databricks to Snowflake, the companies that can help turn raw data into refined insights will be the ones to watch.
As for executives, the message is clear: prioritize data-driven innovation or risk being left behind. Empower your organization with AI, break down data silos, and foster a culture of experimentation and continuous learning. The future belongs to the companies that can harness the power of data to drive intelligent automation, uncover new opportunities, and make smarter decisions at every turn.
We stand at the threshold of a new era of productivity and innovation, powered by the twin engines of big data and artificial intelligence. The companies that can master this dynamic duo will be the ones to thrive in the years ahead. They'll be the ones that truly know what they know – and use that knowledge to change the world.