Name: kdb+ 4.1 Release
Start: 2024-02-27T15:00:00Z
End: 2024-02-27T15:00:53.000Z
Location: BrightTALK
Rating: 5

KX is the maker of kdb+ the world’s fastest time series database and analytics engine. Built for the world’s most demanding data environments, our industry-leading software can process and analyze time series and relational data at unmatched speed and scale for richer insights that drive better business decisions. Capable of running on any cloud, on prem, or at the edge, KX empowers developers and data engineers to build high-performance data-driven applications and turbo-charge their favorite AI and ML analytics tools. KX is trusted by the world’s leading companies across a range of sectors including capital markets, healthcare, manufacturing and telecommunications to deliver business value including risk mitigation, enhanced regulatory compliance, increased machine uptime and rapid development and launch of new products and services. For more information visit www.kx.com.

In a rapidly evolving landscape, trading research continues to grow in significance. As trading shifts towards more dynamic, learning-based models, understanding and measuring the incremental value of trader decisions, strategy behaviour and model outputs becomes even more critical. Effective trading research should not only explain what happened but delve deeper to explore the reasons driving this behaviour and identify actionable insights to improve future trading decisions.  

In this 45-minute interactive virtual workshop, we invite industry peers from both buy and sell side financial institutions to join us in a discussion, including a live analysis demo and Q&A session with industry experts and market practitioners, on how to go beyond measure & interpret your data to address real-world challenges in trading research and execution performance.

Optimize Your Execution: Trading Research Best Practice

KX and BestX join forces to discuss the many tech, regulatory, and market factors that are driving change within Best Execution Analytics. Topics covered include the adoption of the cloud, regulatory changes such as MIFID2 and RG97, and process automation.

As BestX co-founder Ollie Jerome shares: “A lot of our very large clients have gone through a similar process of management change over the last two or three years where now you have folks from an Equity background managing the cross-asset desks, including Fixed Income and FX.”

BestX is a 7-year-old technology company that partners with KX. They deliver Best Execution Analytics to help over 30 banks and almost 180 of the world's largest hedge funds asset managers clients to define, achieve and record a process of Best Execution across FX, Fixed Income, Equities, Commodities, Futures, and Crypto. They currently represent about $45 trillion of AUM (Assets Under Management).

Innovation, Change and opportunities in the world of Best Execution Analytics

“Three Innovative Quant Trading Apps and Three Ideas Everyone Should Steal”, is an interactive exploration of three innovative applications on Wall Street that leverage high-frequency data in creative ways for sense-and-respond intelligent action (trade execution), live-streaming research and strategy (for intraday trade strategy adjustment), and continuous risk management. While these use cases may seem particular to the capital markets, they exist everywhere.

This one-hour session with Conor Twomey (KX Head of AI Strategy) and Mark Palmer (Time Magazine Technology Pioneer) will explore these innovative use cases and explain three ideas everyone should steal in any application area dealing with streaming and historical data, and high-value decision-making in real-time.

Three Innovative Quant Trading Apps and Three Ideas Everyone Should Steal

Innovation, change and opportunities in the world of Best Execution analytics

Quants develop – and help implement - digital transformation within firms. These ideas can change, or even revolutionize, their organization across functions such as trading and risk management. Whatever your area of focus, today’s market unpredictability presents excitement, opportunities, and challenges for quants including: 
• Market volatility driving high volumes of data
• A model building ecosystem centered on the Python programming language
• The increasing use of machine learning
• The rise of cloud and microservices

Join Conan Hales, CFA, CQF, Solutions Engineer, KX and Harry Darell Brown, VP of Product Management for Financial Solutions, KX to explore the challenges and opportunities of Quantitative Research in 2022.

Referencing real-world examples, our speakers will discuss: 
• Why KX insights is the ideal platform for time series data analysis and model 
        development using languages like Python.
• How KX is positioned for the world of streaming data.
• A case study of how KX enabled an exchange to commercialize their unique dataset.

Register today and discover the future of quantitative research.

Quantitative Research Tooling for High Volume Financial Markets  (APAC)

Using Python, and perhaps Pandas? This webinar explains how you can provide production data workloads to your Python code and Jupyter Notebooks, adding 8x to 100x more data power to your models and reducing the time needed to take research into production.

This webinar explores how to: 
• build a data ingestion pipeline
• dramatically transform Python time series workflows and analytics (asof joins; xbar for time series formatting)
• augment and improve your data science in Jupyter Notebook using KX's Python Interface

Watch this webinar to see a demonstration of a computational finance workflow and to understand the same rigor and capabilities that can be deployed to any use case that utilizes Python and highly granular and high-frequency datasets.

kdb Microservices for Ultra-High Velocities on a Postage Stamp Footprint

With decades of combined experience at the sharp end of the Financial Services sector, the panelists discuss the various requirements that make up the perfect platform for trading analytics. In more detail, they’ll explore how a trading analytics solution should:
• Optimize trading outcomes
• Be futureproof
• Deliver Best Execution

The team discuss the opportunities for optimization and its dependency on finding value from multiple data volumes - and how repeatable any optimizations are. The panel also debate benchmarking, data management, application development, data pipelines, transparency, and more through real-world examples. We'll also have a deeper dive into how TCA can be utilized as a tool to help traders and data scientists better understand how their trades performed and can inform strategies for improvement.

Time Series Analytics - Powering Trading Outcomes (APAC)

When it comes to business initiatives driving technology spend, 1 in 3 organizations state that their top initiative over the next 12 months is to improve their data analytics for real-time business intelligence (Enterprise Strategy Group).  

This is largely driven by the fact that when using data to make informed business decisions, it is no longer enough to rely on business intelligence derived solely from historic (big) data. Instead, to keep pace in the digital era, insight must be combined - even supplanted - by continuous real-time data analytics.  

Taking advantage of real-time analytics, however, is not so straightforward. Data is growing, distributed data environments are increasingly dynamic, and with so many vendors and tools to choose from, organizations need help. 

In this discussion, ESG Senior Analyst Mike Leone is joined by Conor Twomey, Head of Customer Success at KX and Kiran Singh, Data Analytics & Data Science Leader at NextEra Energy, to discuss in-depth how organizations can find clarity from the chaos.  

Join them to learn about: 
- The business objectives driving the need for faster decision making through streaming analytics 
- The common challenges preventing success and the capabilities that matter most in streaming analytics platforms 
- What to look for in a modern data platform and how to determine if it is right for your business 
- How the cloud is supporting real-time data initiatives across different industries 
- A customer case study and common use cases for analytics that are delivering proven value for organizations 
- And more

A New Data Frontier: The Value of Streaming Analytics to a Data-first Business

Time Series Analytics - Powering Trading Outcomes

This discussion between Vats Vana, Vice President of IoT Strategy & Products at KX, and guest speaker Paul Miller, Vice President, and Principal Analyst at Forrester, covers several topical issues in Manufacturing, including:

• The catalysts for change – including a need for deeper analytics from ever-evolving Edge communication.
• Trends and challenges in the industrial IoT space.
• The value of contextual data and the importance of understanding how timely insights need to be.
• The connection between insights, decisions, actions, and outcomes.
• The measurable ROI of data analytics from Manufacturing IoT
 
Calling upon decades of experience, Vats and Paul examine the relationships and conflicts between tech, data, people, and processes, the cultural gap between OT and IT, and attempt to establish whether real-time is the right time. 

Through case studies and real-world examples, Vats will lead the discussion on the value of ‘context’ and how rich insights help drive the decisions, actions, outcomes, and change needed for modern manufacturers to survive and thrive.

The Value of Timely Data in Modern Manufacturing

In a world where the smallest margins represent millions of dollars, attempts to manipulate the market are inevitable. And with few regulations governing this “new” asset class, Cryptocurrency markets are no exception and are considered particularly vulnerable to hacking, fraud, money laundering, and other criminal activity. 
 
Justin Handsman, FICC & Derivatives Specialist, KX, and Charles Gregory, VP of Product Management for Surveillance Solutions, join host Steve Wilcockson, KX to explore the challenges, opportunities, and nuances of Trade Surveillance across multiple markets.  
 
Referencing real-world examples, the team discusses:
• The similarities and differences between traditional and digital exchanges, from the exchange and trader point of view.
• Impact of data volume and the difficulties of building the “perfect picture” - compounded by market depth challenges.
• The importance of real-time transactional visibility.

Trade Surveillance in Equities and Crypto Markets

Quantitative Research Tooling for High Volume Financial Markets

Whatever your preferred form of analytics, interface preferences, coding skills, or architecture – cloud, on-premises or hybrid - handling more data more simply is in easy reach. In this session, we will explore, with examples from multiple industries, 3 simple steps data scientists, analysts and their teams can take to run powerful, scalable real-time analytics that reduce compute costs, data complexity, and risks. They include: 

• simplifying data management and storage processes, including real-time data. 
• automating and integrating continuous intelligence that combines new and historical data. 
• customizing code and visualization to drive faster, more useful decisions, commensurate with your organization’s bespoke needs and unique culture.

Streaming Analytics for No-Code, Low-Code or Loadsa-Code

As the financial world seeks to optimize proprietary pricing and trading strategies, the huge volume of tick data demands models that can deal with multi-asset class data and incorporate ancillary data for insights and risk profiling in real-time.

We’re excited to host this webinar alongside ICE, a global leader in cross asset market data, pricing and analytics. We’ll discuss different approaches to optimizing your algo trade models using real-time & historical data analytics  . If you’re making fast decisions using large tick data volumes, then this webinar will help equip you with the tools you need to optimize your tick environment. We’ll explore: 

• The most valued features and functions of a real-time analytical platform.
• Technologies available to build a high performance, flexible DataOps environment to derive maximum value out of your tick data.
• Backloading historical data to validate trading models before deploying them to production using real-time data.
• The market trends amongst buy-side and sell-side, and the importance of high-quality market data to an alpha-generating model across listed and OTC assets.

Expert Speakers:
• Martin Haines, Managing Director, Asia, KX
• Leon Liang, Director, Feeds Business Development, ICE Data Services

Optimize your algo trading models: Tick data best practices

Making quick and contextual decisions in real-time is the new frontier in a manufacturing sector going through rapid modernization….
 
However, discrete and process manufacturers face many challenges along this modernization journey – learning best practices from a pandemic that has not yet passed, overcoming supply chain disruptions, rising component and commodity prices, fluctuating energy prices, geopolitical unrest, and reducing the costs of stricter environmental and legislative regulations.
One thing manufacturers are not short of - is data. It oozes from every sensor, machine, process, plant, supplier, and customer. But few manufacturers can effectively consolidate or manage their data, let alone extract the value and insight needed for decisions that drive productivity or efficiency gains.
 
Utilizing and connecting the dots across all available data from any source and any location - in the cloud, on-premise, and at the edge - in real-time, opens the door to immediate efficiency gains and accelerates your journey to enhance business agility and customer experience. This webinar explores the trends driving innovative thinking within the sector and will present four ways that you can find the efficiencies you need through real-time data.

Host: 
• Nick Laurence, Vice President, Marketing Communications, KX

Manufacturing evolves: How real time analytics drives better business outcomes

KX is excited to be joined by leading Principal Analyst Mike Gualtieri from Forrester to discuss how the new real-time data frontier is shaping digital business. Mike is well versed on AI technologies, platforms and practices that enable technology professionals to deliver applications that lead to better digital experiences and breakthrough operational efficiency. As businesses become more dependent on real-time data to make critical decisions, they are often challenged to achieve the required business value when its needed most.
 
Challenges arise from complex infrastructure, a lack of data skills, disparate data silos, an inability to scale, and difficulty analyzing data in context. In this webinar, you’ll learn how streaming analytics platforms are built from the ground up to address these challenges to deliver on the promise of rapid real-time decision making. We will focus on the importance of interoperability and why having a single integrated platform is key in the role of delivering speed to business value in a modern data landscape that’s built for real-time.

Hosted by: Nick Laurence, VP, Marketing Communications, KX

Real-time data use cases: 7 key questions your business must ask

KX is joined by Queens University Belfast to discuss how data science is accelerating innovation and impacting the evolution of the “smart factory”.
 
The presenters will explore a variety of opportunities and challenges within the manufacturing industry today including:

* how to optimise process efficiency i.e. machine learning, equipment tooling etc
* how brownfield connectivity can add new value to older in-situ equipment
* how a “digital-twin” can accelerate the adoption of Industry 4.0
 
This episode will also examine why manufacturers are turning to academia for research, and how a data and analytics-driven future could modernize manufacturing into a truly digital industry.

Speakers:
Peter McToal – Digital Lead, Queen’s University Belfast 
Gary Connolly - Senior Business Development Manager – Industry Solutions, KX

How Data-driven Innovation is Modernizing the Manufacturing Sector

KX is joined by Google Cloud to discuss how one of the world’s leading tier-1 financial institutions is building a modern real-time data platform by migrating critical applications to the cloud to accelerate its business decision-making.   
  
Facing a challenging business environment with strict trading protocols, increasing risk and regulatory requirements, rising storage infrastructure costs and an increasing inability to react to dynamic market conditions, the bank needed a new solution that could meet the needs of a modern digital banking architecture.   
  
In this session, our expert panel will discuss: -   
  
• the tools needed to deliver real-time decision making on GCP  
• the benefits of moving to containerized, workloads and services for simple migration  
• how to build a path towards Kubernetes as a portable open-source compute engine platform  
• tips for scaling applications seamlessly in the cloud-based on-user demand  
 
This webinar will provide the simple steps and expert advice needed to deliver cloud-native real-time decision-making on GCP whatever sector you’re in. 

Speakers:

Kyle Corcoran, Cloud Developer, KX
Ronan Carter, Client Partner, FinTech, Google Cloud
Efstathios Onasoglou, CFA Customer Engineer, Capital Markets, Google Cloud

How to Build a Modern Real-time Data Platform

With the announcement of kdb+ 4.1, we’ve made significant performance, security, and usability updates, empowering developers to turbocharge workloads, fortify transmissions, and improve storage efficiency. 

In this webinar, Andrew Wilson will explore these new features and demonstrate how they compare to previous versions:
• Multithreaded data loading
• Parallel processing enhancements
• Unlimited network connections
• Persistent HTTP connections
• Enhanced TLS features
• Improved at-rest compression
• New language features

The webinar will also have a Q&A session following Andrew's demonstration.

kdb+ 4.1 Release

Timeseries

Big Data Analytics

Data Analytics

trading Analytics

Capital Markets

Fintech

Machine Learning

Data Architecture

Data Science

Data Ops

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kdb+ 4.1 Release

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