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September - 2014 - issue > CXO View Point
Situational Intelligence Big Data Solved
Jagadeesh Macherla
VP of Engineering & Chief Architect-Space- Time Insight
Monday, September 1, 2014
Space-Time Insight's situational intelligence enables companies to make real- time decisions and also helps analyze their resources across location and time, and rapidly respond to disruptions in service. Founded in 2007, headquartered at San Mateo, CA, the cinoaby has raised a total funding of $42 million from Novus Energy Partners, ClearSky Power & Technology Fund, Opus Capital, Start Up Farms International and Zouk Capital.
The Problem with Big Data
"Big data" is more than a buzz word today - it reflects both an opportunity and threat to businesses across the globe. By some estimates, up to 35 zettabytes (or 35 times 1021 bytes) of data will be generated annually by 2020. From a tidal wave of individual spreadsheets to enterprise-wide systems to real-time machine feeds from geographically-distributed assets and third party sources, organizations are awash in data, and seek a means to convert this data into useful information.

Imagine you run a railroad today and need to make decisions based on data about fuels, engines, rolling stock, cargo, staffing and wages, passengers, schedules, weather, track conditions, and on-going construction, not to mention the contracts, laws and regulations pertaining to the rail business. All this data could be very useful, presenting a real opportunity to save costs, increase revenues, and develop new services. Or, it could obscure significant risks to people, property, and profits; in other words, a serious threat.

Traditional business intelligence and analytics tools are proving to be insufficient to the task. Big data stems from events, assets, and resources across locations, in varying times and time intervals, and in unrelated meanings depending on the context in which the data occurs. Big data comes in structured, semi-structured and unstructured formats, arrives in disparate intervals from discrete systems, and lacks a common presentation format. This combination of challenges calls for a new approach to find meaning in data.

A New Solution: Situational Intelligence
Forward-thinking organizations are turning to a new type of software called situational intelligence. Situational intelligence interprets data across operational, business, social, machine, location and environmental domains. Situational intelligence software helps all types of users - business, operations, and technical - by forming a bridge across the many challenges of big data: providing real-time access to single view into data correlated from disparate systems that comes in diverse formats, and most importantly, within the context needed to support crucial business decisions.
Situational intelligence correlates and analyzes big data and visualizes it in a way that doesn't require advanced knowledge of typical analytics tools. Situational intelligence software truly makes the information actionable, not just detecting the condition, abnormality or crisis, but identifying the optimal recommended action to remedy the situation and providing the ability to take immediate action as appropriate.
How does a typical situational intelligence solution work? Generally, there are three types of actions that the solution takes.

1. Data collection and integration
The situational intelligence software collects and normalizes historical, real-time (current) or predictive (future) data from across the enterprise and beyond.

2.Data correlation and analysis
With the big data collected and normalized, context can be understood through correlations and analysis, then applied to support enterprise decisions.

3.Data visualization
An actionable visualization of analyzed information combines all aspects of the information into an easy-to-understand display that can be quickly put to use by non-technical staff.

What the Market is saying about Situational Intelligence Software
Situational intelligence applies to a wide range of industries including utilities, oil and gas, telecommunications, transportation and logistics, government, and more. Situational intelligence solutions address challenges across diverse business functions, including:

1 Identifying performance abnormalities over time and taking proactive steps to maintain assets or solve situational threats
2 Correlating real-time and historical data streams from multiple sources to identify areas for optimization
3 Prioritizing tasks based on their projected financial benefit to the company
4 Planning for and rapidly responding to the effects of a severe storm on an enterprise's infrastructure
5 Balancing the variability of power generation with the demands of customers
6 Analyzing why an asset malfunctioned and triggering remedial actions as a result
7 Feeding failure information proactively to customers to reduce service inquiries and social media backlash

Businesses face an enormous challenge dealing with the amount and complexity of data created by and about their enterprise. If left unmanaged, the volume and variety of data makes correct decisions about operations, events and crises almost impossible. When business users and technical personnel receive accurate and timely information in a user-friendly and easy-to-understand visual format, they are able to make informed real-time decisions to improve the effectiveness of the operations in their area. Situational intelligence solutions integration, correlate, analyze and visualize big data, improving the ability of staff to make business-critical decisions that can generate opportunities for growth and profit.

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