Crunch 2015: The Nexus of Big Data, AI and Business Impact

2015 is shaping up to be a landmark year for big data and artificial intelligence. As enterprises seek to extract more value from their data assets, the demand for scalable, cutting-edge analytics has never been higher. Increasingly, this means looking to emerging technologies like AI and machine learning to surface insights and drive better decisions.

It‘s against this backdrop that the Crunch Practical Big Data Conference will bring together over 500 data scientists, engineers and executives for three days of intensive learning and networking in Budapest. Now in its inaugural year, Crunch is quickly establishing itself as one of Europe‘s premier big data events, boasting a speaker lineup of industry thought leaders, top practitioners and innovative startups.

AI and Machine Learning Take Center Stage

While big data has been a hot topic for several years now, what sets Crunch apart is its focus on the technologies poised to disrupt the field for years to come – namely artificial intelligence and machine learning. The conference agenda is replete with sessions showcasing how leading companies and researchers are leveraging AI/ML to push the boundaries of what‘s possible with massive datasets.

Recommendation engines have become a "killer app" for machine learning, and Esh Kumar (Spotify) and Andras Benczur (SziMe) will be on hand to share their experiences building and optimizing these systems at scale. With ML-powered recommendations accounting for over 35% of Amazon purchases and 75% of Netflix viewing activity, the impact of this technology can‘t be overstated.

Of course, AI/ML isn‘t just for consumer-facing applications. Numerous talks will explore how algorithms and predictive modeling can be applied to thorny enterprise challenges like fraud detection, customer churn and dynamic pricing. Companies like Skyscanner are using machine learning to more accurately forecast demand and optimize ticket prices in real-time – a compelling example of AI delivering bottom line results.

But beyond individual applications, Crunch will also zero in on the platforms and architectures needed to operationalize data science and AI/ML at scale. Attendees will hear detailed case studies on how companies like Pinterest and Prezi have architected their big data stacks to support the unique demands of machine learning workloads. Sessions will cover key considerations like choosing between batch vs. streaming processing, leveraging the cloud for elastic workloads, and establishing feedback loops between online and offline models.

Bridging the Gap: Big Data Meets Traditional Enterprise

While the promise of AI and big data is immense, the reality is that most enterprise data still resides in traditional IT systems. Bridging the gap between the data science world and mainstream enterprise infrastructure remains a major challenge. Crunch has recruited an impressive roster of speakers from industry heavyweights like Cloudera, Hortonworks and Teradata to share best practices for navigating this divide.

Stephen Brobst, CTO of Teradata, will share his perspective on the architectural patterns for supporting data science workloads in large enterprises. Other sessions will dive into the nuts and bolts of ‘bootstrapping‘ big data projects on legacy infrastructure with technologies like Hadoop, Spark and Kafka.

With major vendors racing to build solutions at the intersection of traditional databases/data warehouses and big data, Crunch is an ideal venue to learn about the latest product developments and how they fit into the modern enterprise data ecosystem. Expect to see lively debate on the merits of SQL vs. NoSQL, the role of the cloud, and strategies for unifying data silos.

The Business Impact of Big Data

At the end of the day, big data and AI initiatives are only valuable if they deliver meaningful business results. Crunch puts a strong emphasis on real-world case studies and ‘war stories‘ that demonstrate the impact data-driven decision making can have on key metrics and KPIs.

Andrea Burbank from Pinterest will share how the company leverages vast amounts of user data to derive insights and build products that delight their 250M+ active users. SurveyMonkey reduced churn 20% by applying machine learning to its trove of customer usage data – Director of Growth Elena Verna will explain how they did it. Hortonworks will showcase several examples of companies that have used its big data platform to transform key business processes and unlock new revenue streams.

Big data has clearly gone mainstream in the business world:

• 97% of organizations are investing in big data and AI
• By 2025, data-driven organizations will be 23x more likely to acquire customers, 6x more likely to retain them, and 19x more likely to be profitable
• The global big data and business analytics market is expected to reach $274B by 2022, up from $166B in 2018

As the data clearly shows, companies that aren‘t investing heavily in data and AI capabilities will quickly fall behind the competition. Crunch aims to arm attendees with the insights and know-how needed to drive data-enabled business transformation at their organizations.

Why Budapest? Central Europe‘s Data Science Boom

The choice of Budapest as host city for Crunch is a reflection of the rapid growth of big data and AI throughout Central and Eastern Europe (CEE). With a highly-skilled technical workforce, budding VC investment scene and proximity to other EU tech hubs, the CEE region has become a hotbed of data science activity.

Hungary in particular has made major strides to establish itself as a big data leader. Budapest is home to one of Europe‘s top data science masters programs at the Central European University and has spawned successful analytics startups like Prezi, Starschema and Logmein.

The capital city also boasts a thriving data science Meetup scene and has hosted satellite events for global big data conferences like Spark+AI Summit and Big Data Tech Warsaw. With companies like Cloudera, Hortonworks, Talend and Iflexion opening up offices in Budapest to tap local data science talent, the city is cementing its status as an analytics hub.

Crunch organizers Prezi and Ustream are deeply committed to nurturing the local tech ecosystem and showcasing the region‘s thought leadership on an international stage. Attendees can expect exposure to fresh perspectives and ideas from the CEE data science community and build valuable relationships with practitioners working in one of Europe‘s most dynamic economies.

The Road Ahead for Big Data

As data continues its relentless growth and AI goes mainstream, it‘s more critical than ever for data professionals to stay on top of the latest tools, trends and best practices. Crunch delivers forward-looking content that will help attendees navigate the rapidly-evolving big data landscape and capitalize on emerging opportunities.

Crunch will offer a glimpse into the future of several key areas of innovation:

• Feature Stores: The next frontier for productionizing machine learning is providing data scientists with a centralized, real-time repository for feature engineering. Uber, Airbnb and Netflix have pioneered this concept but a new wave of startups like Hopsworks and Tecton are making it accessible to the masses.

• Edge Analytics: With the proliferation of IoT devices, drones, autonomous vehicles and 5G networks, massive amounts of data are being generated at the edge. The next wave of data architectures will be optimized to ingest, process and analyze this sensor data in real-time at the point of collection. Talks at Crunch will address strategies for distributing data science workloads and maintaining model accuracy in resource-constrained edge environments.

• Data Privacy & Ethics: The public‘s faith in big data and AI was shaken by high-profile scandals at Facebook and Equifax. At the same time, GDPR ushered in a new era of regulatory oversight for data-driven businesses operating in the EU. Sessions at Crunch will grapple with the ethical dimensions of big data and offer guidance on building responsible, transparent AI systems that put privacy front and center.

• Augmented Analytics: As data volumes scale beyond the capacity for manual analysis, organizations will increasingly turn to AI-powered tools to automatically surface insights, explain anomalies and optimize business processes. Big data vendors are racing to incorporate natural language processing, conversational analytics and other automation capabilities into their platforms. Crunch will be an ideal venue to discover the latest product innovations enabling the next phase of data democratization.

Beyond these key themes, Crunch promises to be a lively forum for debate and knowledge sharing on all things big data. Whether it‘s the new tools for doing scalable machine learning like H20, Mlflow and Kubeflow or strategies for attracting talent amid the worsening data science skills gap, expert speakers will weigh in on the issues keeping data leaders up at night.

Conclusion

When the book is closed on 2015, there‘s little doubt that Crunch will be remembered as a pivotal gathering for Europe‘s data science community. At a time when enterprises are racing to implement AI and machine learning solutions, Crunch offers a deep dive on the tools, architectures and business strategies needed to stay ahead of the curve.

Over three days, attendees will soak up practical insights from the brightest minds in data – not to mention forge valuable connections with fellow practitioners working on the frontlines of the big data revolution. They‘ll return to work energized with fresh ideas and armed with the know-how to take their organization‘s data and analytics capabilities to the next level.

Tickets are still available but won‘t last long. If you‘re serious about data, Crunch is quite simply an investment you can‘t afford to miss. See you in Budapest!