Merging Data Visualization with Operational Intelligence
This is the continuation of the transcript of DM Radio’s program titled “What You See Is What You ‘Get’ – How Data Visualization Conveys Insight,”
Eric Kavanagh: Right. Okay, folks. Moving right along, our next guest some of you who have been around for while may recognize the name as a co-founder of that company called TIBCO. It is a prominent player in the world of enterprise technology these days. Dale Skeen now the head of Vitria -- welcome to the DM Radio.
Dale Skeen: Oh thanks, Eric, thanks for having me today.
Eric Kavanagh: Sure thing. So I know you guys focus on operational intelligence such as streams of data, understanding what’s going on, and what you can do about it. How does data visualization fit into that world?
Dale Skeen: Actually, I think operational intelligence starts and stops with visualization. When we look at operational intelligence there are about three capabilities.
The first is the visibility of the data itself. This is actually because we’re looking for operational data from systems that can be your transactional systems. It’s not always apparent or recorded. You first have to be able to extract that information just to make the raw data physical.
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Add Insight to Analytics with Context
But to add insight to that you have to add analytics and, more importantly, context -- whether it’s a business context or if you are looking at a transaction then process context. And you have to do it in a way that makes sense to the dashboard users. So, data visualization starts with just seeing the data. Then with operational intelligence you can also add the insight and the ability take action to that.
Eric Kavanagh: Yeah and so what are some examples of things that you might see if you are focused on analyzing what's going on in your organization? Obviously a new number of industries come into mind -- certainly financial services -- but what are some good examples of what someone might see through a visualization tool? Then what would they do about it?
Dale Skeen: Well typically we focus more on the real time aspect of the business. These are things that you won’t monitor because seconds to minutes count. The financial trading situation you just mentioned is a good example.
For instance, look at buying to trades risk. Another example is security -- whether cyber security or physical security. So there you may want to look at anomalies--people are trying to log in, maybe want to look at the higher level, the incidences such as how inflation is spreading. You want to have visualization that shows relationship between the entities whether it's the hackers or if the machines themselves are being compromised.
A lot of times we see that our customers are trying to visualize what's happening with their business transactions because for a lot of Indian business transactions, for example, it is automated in multiple systems.There is no view of what’s going on. And so they won’t visualize that and then relate that to a context of process objectives as well as business objectives or business goals.
Visualizing Stock Trades: Techniques and Tools
Visualization plays a critical role in helping investors, analysts, and algorithmic traders make sense of complex stock market behavior. Stock trades generate large volumes of granular data—price movements, volume, bid-ask spreads, order book depth, execution times—that are often difficult to analyze using spreadsheets or raw tables alone. By transforming this information into visual representations, traders can identify patterns, spot anomalies, and act on market signals faster and with greater confidence.
Stock trade visualizations are not just for high-frequency trading desks. From retail investors looking at candlestick charts to institutional quants monitoring tick-level liquidity, the right visualizations can turn noise into actionable insight. This article explores the key types of visualizations used in stock trading, their use cases, and the tools best suited for real-time and historical market data analysis.
Candlestick Charts and OHLC Plots
One of the most common visualizations in stock trading is the candlestick chart, which encapsulates open, high, low, and close (OHLC) data over a time interval—typically minutes, hours, or days. Each “candle” shows the price range for the period, where the body reflects the difference between the opening and closing price, and the wicks represent the intraday highs and lows. Candlestick patterns, such as dojis, hammers, and engulfing candles, are frequently used by technical analysts to gauge momentum and potential trend reversals.
Closely related is the OHLC bar chart, which uses vertical bars instead of filled candles but conveys the same information. These charts are foundational for visualizing price movements over time and are often enhanced with overlays such as moving averages, Bollinger Bands, or RSI indicators.
Volume Charts
Volume is a critical component of any trading strategy. Visualizing trade volume—the number of shares or contracts exchanged in a given period—helps traders understand market liquidity, interest in a particular stock, and confirm price trends. Spikes in volume often accompany breakouts or breakdowns, providing traders with confidence to enter or exit positions.
Volume can be plotted as vertical bars under a price chart, color-coded by buying or selling pressure. Some platforms also offer volume profile charts, which show traded volume at various price levels rather than over time, highlighting zones of support and resistance.
Order Book and Level II Visualizations
For active traders and quants, the order book — displaying current buy and sell orders (bids and asks)—is essential for understanding market depth and sentiment. Order book visualizations often take the form of tables, but more advanced platforms convert them into depth charts that show cumulative bid/ask volume as a curve or histogram. These visualizations help detect liquidity gaps, spoofing patterns, or the presence of large institutional players.
Level II data, or market depth, reveals all orders beyond the best bid and ask. Visualizing Level II data requires tools that can handle high-frequency updates, and often includes heatmaps to highlight order flow pressure or shifts in momentum.
Tick Charts and Time and Sales
Tick charts plot trades as they occur, rather than at fixed time intervals. This is valuable for scalpers or algo traders who need to act on microstructure dynamics in real time. By visualizing trades per tick, one can see the pace of activity and detect bursts of high-frequency trading or large block trades.
Time and sales (also known as the tape) is often visualized as a scrolling stream of executed trades, with price, volume, and timestamp. Enhanced versions highlight trades that happen at the bid or ask, showing whether the market is being lifted or hit aggressively.
Advanced Techniques and Tools
Modern trading platforms and data visualization libraries now allow for more sophisticated visualizations, such as:
- Heatmaps of stock performance across sectors
- Correlation matrices between stock returns
- Real-time dashboards integrating technical indicators, market news, and trade alerts
- Graph-based visualizations to show relationships between market participants or stocks
Popular tools for building these include TradingView, ThinkorSwim, MetaTrader, and developer-centric options like Plotly, D3.js, or Python libraries such as Matplotlib, Bokeh, and Dash. For real-time data, and a ready to use platform that can access WebSockets and streaming APIs to keep visualizations live and interactive, StyleBI is a good option.
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