Learn how the world’s top energy and utilities companies use KX time series and vector native data analytics to optimize trading strategies and increase visibility from sensors on turbines, mission-critical smart meters, buildings, solar panels, gas pipelines, and other industrial IoT infrastructure for better outcomes.

The digitization of the energy and utilities industry is driving unprecedented growth and an explosion of data. When harnessed, energy and utilities companies can make informed decisions, optimize resource allocation, and predict demand fluctuations, improving operational efficiency. Vector native data analytics in particular helps navigates high-dimensional data to uncover complex relationships and correlations. With KX time series, AI and vector database analytics, companies can identify opportunities for renewable energy integration, to optimize distribution networks, and implement effective demand response strategies.

BENEFITS

ACCELERATE DATA ANALYTICS OUTCOMES ACROSS MULTIPLE ENERGY AND UTILITIES INDUSTRY USE CASES

Optimize Energy Trading Outcomes at Scale

Built on Wall Street, trusted on Main Street. Optimize trade performance, reduce risk and improve ROI. Forecast supply and demand, navigate price movements in real-time, and query data from trading venues and databases.

Deliver High-performance Industrial Automation

Process high-speed data streams from wind turbines, and power plants for real-time monitoring of energy consumption and generation demand forecasting, smart meters, fault detection, and other critical operational tasks.

Predict Maintenance Schedules and Faults

Observe critical infrastructure with insight across the energy and utilities grid. Schedule routine workloads when optimal, and perform predictive maintenance to reduce equipment breakage, increase uptime and provide better service.

KX Spotlight:
Utilismart Corporation

Operating out of Ontario, Canada, Utilismart delivers a digital utility platform to empower over 140 utilities across Canada, the United States, and the Caribbean to unlock smart-grid technologies – enabling real-time decision-making and maximizing operational efficiencies, reliability, and service flexibility. Read the case study here.

Miroslav Karlicic, VP Business Development and Innovation, Utilismart Corporation

01

Store, ingest and manage data from multiple sources at speed and scale.

02

Facilitate AI simulation and modeling, back test hypotheses and deploy predictive analytics at scale.

03

Combine historical temporal vector data with real-time data streams.

04

Get insights to machine operators, data scientists and energy grid practitioners faster.

05

Generate analytics at the edge with low-cost compute resource to maximize space.

HOW KX ENRICHES THE ENERGY AND UTILITIES MARKET
WITH DATA

HOW KX ENRICHES THE ENERGY AND UTILITIES MARKET
WITH DATA

Why kdb for Vector and Timeseries Use Cases in Energy & Utilities?

As a vector database and time series analytics engine, kdb processes and analyses massive data volumes quickly and efficiently, making it ideal for developers, data engineers and data scientists. kdb’s built-in functions, including aggregations, joins, and machine learning, optimization, statistical and search algorithms, allow analysis, modelling and reporting at scale of energy markets, smart meters, control systems, equipment performance, system observability and reliability and more. Discover more here about why kdb is so fast and efficient.

KX: THE NEXUS FOR ENERGY & UTILITIES

PERFORMANCE - FAST AND PROVEN TECHNOLOGY

Ideal for addressing performance and scalability challenges of high-volume data ingestion, processing, retrieval, analytics, and machine learning, kdb is proven to validate and estimate sensor and smart meter data at millions of readings per second.

kdb can also aggregate billions of measurement records in seconds and store and analyze trillions of records and diverse data sources. Customers have benefited from:

  • 10X to 500X improved performance.
  • 90% less infrastructure cost.
  • lower total operating costs with improved scalability.
  • reduced time to market through proven big data technology and expertize.
STAC Summit 2022 Unlocking Advantage with Cloud Driven Architecture blog - KX
ADVANCED ANALYTICS AND BI-TEMPORAL MODELLING

Many companies today use less than 10% of the sensor data they collect. They struggle to keep up with Validation, Estimation and Editing (VEE) processes needed to support big data analytics systems because of the high volumes and velocities of data.

To combat VEE system overload, KX provides VEE and analytics capabilities to ingest, validate, estimate, and analyze massive amounts of streaming, real-time and historical data from sensors, devices, and other data sources.

kdb also enables bitemporal modelling of sensor data and attributes with nanosecond precision, enabling rapid navigation across time for continuous analytics, avoiding the need to pause, and ensuring forensic auditability and traceability of data updates.

Single Data Store - KX
DISTRIBUTED AND RENEWABLE ENERGY RESOURCES (DER) MANAGEMENT

KX is particularly useful for utilities looking to better manage DER – such as solar panels, electricity storage, electric vehicles, and other controllable loads – given the intermittency and variability of the outputs.

Integrated, continuous data analytics can also simplify situational awareness for other types of energy asset management – linking SCADA, micro-phasor and behind-the-meter data, to predict the condition of the power system and enable maintenance.

Due to its small footprint KX can provide big data analytics close to where data is collected, including on the edge, enabling utilities and solution providers to detect and predict conditions more quickly, improve availability, optimize maintenance, and increase asset longevity.

SEAMLESS INTEROPERABILITY

KX integrates with legacy systems and multiple data sources, for example augmenting or replacing historians and allowing for immediate customization.

Use connector frameworks to integrate with IT/OT systems, including:

  • SCADA, AMI, MDM, OMS, MDM, EMS, and ADMS.
  • APIs for .NET, Java, C, C++, Python, R, ODBC, MATLAB, and Excel.
  • APIs for synchronizing master and reference data with other systems, including assets, locations, sensors, and sensor measurements, with built in-audit trails.
Network of sensors
ADVANCED SUSTAINABILITY
Monitoring, and proactive prevention of environmental and ecological breaches within processes can significantly reduce regulatory penalties and reputational damage.

Being able to leverage real-time insight for better use of resources, extending the effective equipment and machinery reliability, detecting breaches, reducing waste, and reducing re-work all combine to represent a measurable and credible sustainability initiative.

In addition, use 10X to 100X more efficient kdb infrastructure when compared to traditional warehouse, lake and lakehouse infrastructures for common analytics queries.

Reliability and Validity of Data - KX
FORRESTER STUDY

Total Economic Impact™ of kdb Insights Enterprise

Forrester’s Total Economic Impact™ study examines the return on investment organizations can realize by deploying kdb Insights Enterprise for time series and vector native analytics. Download the study to learn more and discover how.

Read the Study

KEY RESOURCES