In the News
In 2019, the world of AI and analytics will need to converge in order to drive more meaningful business decisions.
Data engineers will find themselves in high demand – they specialize in translating the work of data scientists into hardened, data-driven software solutions for the business.
In 2019, AI will be an essential part of the marketing strategy.
The rise of the data engineer brings AI to the forefront of the enterprise.
"2019 is the year of the data engineer. Data engineers will find themselves in high demand—they specialize in translating the work of data scientists into hardened, data-driven software solutions for the business."
Enterprises which integrate advanced analytics and machine learning and the cloud into their data analytics and insights programs are reaping the most from their data.
As data sets have grown, rendering large amounts of data with traditional architectures has become harder, said Nima Negahban, CTO and co-founder at Kinetica. GPUs used with direct memory access can help crunch large volumes of data faster and more efficiently. This makes it easier to build high-definition visualizations on the server side that simply get served by the application via a web application.
Independent Research Finds Traditional Analytical Platforms Struggle to Quickly Deliver Data Insight
Study reveals that enterprises are in urgent need of new modern data architectures to drive faster analytics and business decisions
Kinetica, the insight engine for the extreme data economy, has delivered a GPU-Accelerated Analytics Engine to SoftBank Corp. a subsidiary of SoftBank Group Corp.
IDC Names the 13 Outstanding Digital Leading Organizations in Asia Pacific at the Regional IDC Digital Transformation Awards 2018
OVO wins Asia/Pacific Digital Trailblazer of the Year and Digital Disruptor of the Year
Big data is de driver achter veel innovaties in de IT-industrie. Met de juiste hulpmiddelen kan uit big data veel informatie gehaald worden.
Data Analytics made in USA
Kinetica, an extreme data database doped with GPUs
Das Unternehmen entwickelt eine Plattform, die Datenbanken durch den Einsatz von GPUs in Echtzeit durchsuchen, auswerten und visualisieren könne. Sie sei besonders für Kunden mit sehr grossem Datenaufkommen und komplexen Anwendungsszenarien geeignet.
Telkomsel, a leading telecom operator in Indonesia, has selected Kinetica to improve data-driven customer experiences.
Indonesian operator Telkomsel has selected Kinetica to act as a converged engine for accelerated analytics, location-based visualization and artificial intelligence.
Kinetica moves up to #7 on the Impact 50 List!
Given the demand for rapid graphical display of data analysis, the GPU-based technologies ought to have an audience beyond video gamers and animation lovers
Nima Negahban, CTO and Co-founder, Kinetica, talks to ReadITQuik about Big Data, Extreme Data and how to best navigate this time when businesses are faced with an explosion of data from all sources.
"We’re excited to partner with NVIDIA in this journey to democratize AI — with NVIDIA driving model development and training and Kinetica driving operationalization and deployment of those models, enabling enterprises to gain maximum insight from their data.”
As time goes on, Kinetica’s Negahban agrees in-memory technology will continue to expand and evolve and move toward what some call the data gravity theory.
Dan Woods sits down with Michael Mahoney, VP of Worldwide Solutions Engineering at Kinetica, to discuss the steps companies need to take to become data-powered organizations.
Tech Blog Writer Neil Hughes spoke with Kinetica CEO Paul Appleby in the latest episode of his podcast
We live in a new era where everything that CMOs do is data-driven, says Daniel Raskin, CMO at San Francisco-based startup Kinetica. And the businesses that can most effectively leverage the use of data will come out ahead by offering a better customer experience.
Now that we’ve barreled past this era and into the Extreme Data Economy, businesses—and even whole economies—are becoming powered by data, so much so that the data generated from conducting business can become more valuable than the actual business itself.
The database world is no longer "flat" with only SQL databases, batch processing ETLs, and solutions that only the top skilled database engineers and data scientists can leverage.
Data is the glue across all channels, and companies will need to embrace business-differentiating data innovations, from artificial intelligence to using super-fast GPUs, that meet customers wherever they are.
Where we go next will be interesting. Kinetica already invites data scientists to bring their ML and Deep Learning (DL) model to its platform for productionizing and operationalizing.
There is more data coming back to and being generated by organizations than ever before and it will only get more complex. This means that organizations need to think about how to simplify their data architectures to grow and thrive in the extreme data economy
Kinetica Maps Future of Automotive Sector; Delivers Analytics and Artificial Intelligence Across Connected and Autonomous Vehicle Value-Chain
With location analytics playing a key role in connected and autonomous car use cases, Kinetica also announced a new Mapbox integration which it will release to the open source community.
Kinetica, an insight engine for the Extreme Data Economy, is taking steps to bring advanced analytics, artificial intelligence and its GPU engine to the global automotive industry.
OVO’s OVO Analytics named as Digital Disruptor of the Year. As part of Lippo Group, OVO provides highly personalized offers and services through a big data analytics platform that integrates information from organizations under the Lippo Group. T
Kinetica is empowering automakers, suppliers, and associated start-ups to speed up how vehicle data insight is engendered by bringing together the accelerated analytics of a GPU database, real-time location intelligence, and the competency of artificial intelligence.
The company announced today that it is becoming a silver member of The Linux Foundation and a bronze member of Automotive Grade Linux (AGL).
The following are Stevie Award winners in The 2018 International Business Awards.
A single engine leveraging GPUs can bring AI to traditional analytics cost-effectively, achieving a healthy return on investment.
With Kinetica, PubMatic can empower our customers with real-time reporting and a sophisticated ad pacing engine.
Automotive Grade Linux (AGL), a collaborative cross-industry effort developing an open platform for the connected car, is announcing that six new members have joined the project including Kinetica.
What skills do developers need to be proficient on AI projects?
The Power Of Location And Time: How Digital Businesses Can Use Location Intelligence For Competitive Advantage
What businesses may not realize is that location and time data can play a foundational role in digital transformations.
With this increase in data sources and complexity of analysis, the key question for operators is: how can you leverage this extreme data to retain customers, improve and expand your business operations?
An insight engine, with a GPU database at its core, combines Advanced Analytics, visual discovery, location intelligence, and Machine Learning within a single engine. All these capabilities will be needed for increasingly complex analysis and conducting IVA at scale.
Data has essentially become the new currency for telecom operators.
Kinetica comes in at #8 on latest insideBIGDATA IMPACT 50 list for Q3 2018 (in order of most impactful)
Daniel Raskin, CMO of Kinetica–a company that develops database management systems, discussed improving the human-machine relationship in order to gain better insights from data.
In the age of extreme data, businesses need to move beyond being informed or validated by data to being powered by data.
Data analytics is a hot field, and ActualTech Media CEO Scott D. Lowe interviews a company on the bleeding edge — Kinetica, a data analytics company with an interesting twist.
Daniel Raskin, CMO of Kinetica, stops by the Adobe Think Tank to talk AI & how we can improve the human & machine relationship to gain better insights from data.
The advent of graphics processing units (GPUs) and their processing power, memory and storage advancements enables certain endpoint devices to aggregate analytics themselves.
Winners - 13th Annual 2018 IT World Awards
IoT requires an insight engine powered by GPUs that analyze data simultaneously in real time.
A new generation of GPU-powered databases has emerged, driven by digitalization and data analytics.
San Francisco-based Kinetica, an instant insight engine provider for the extreme data economy, has named Michael Mahoney as worldwide vice president of solution engineering.
Kinetica named a top 100 company in the data space
Dell EMC OEM Solutions and Kinetica have signed an OEM agreement that will allow Kinetica’s bundled data analytics solution to be available on Dell PowerEdge servers with NVIDIA GPUs.
Data insights company Kinetica expanded on its partnership with Dell EMC this week. The two have collaborated to offer a bundled solution to help clients quickly gather actionable insights from raw data.
Kinetica Announces OEM Agreement with Leading Technology Solutions Provider for Tackling Extreme Data
Joint solution with Dell EMC OEM Solutions enables enterprises to process massive data sets and create actionable insights by combining acceleration hardware with an NVIDIA GPU-accelerated database, machine learning and visualization engine.
Adobe interviewed several AI experts in their Glass Tank at the O’Reilly AI Conference including Kinetica CMO, Daniel Raskin.
Kinetica named SD Times 100 'Best in Show' for Big Data and Analytics
Advances in connectivity, data management, analytics, and machine learning now give us the tools to deliver on the promise of the smart grid.
What’s the most powerful tool government has to improve the lives of its citizens? Data, hands down.
“GPU technology means faster chips, and that enables faster analytics that would normally take exponentially longer to process,” Gene Lee, Chief Analytics Officer at Caesars says. “For real-time analysis, Kinetica is our Manhattan real estate.”
Next-generation solutions, such as GPU-accelerated databases like Kinetica, are reshaping the pharmaceutical and healthcare industries.
Here are four ways the logistics industry is able to address the challenges presented by the growing unpredictability of data and the increasing complexity of analysis in the Extreme Data Economy
Aims to help clients to understand the benefits of using a GPU.
Seems Like We Should All Thank Cloudera, Tamr, Zoomdata, Trifacta, Kinetica For Helping GSK Help Humanity
The foundation of the GSK platform is based on Cloudera, Tamr, Zoomdata, Trifacta, Kinetica.
So where do you begin to address the data and analytics challenges presented by a centuries old company and leapfrog ahead to a place where efficiency can accelerate drug development?
The most lucrative use cases for the IoT require acting in real time on continuously generated streaming data from sources like industrial equipment sensors, autonomous or connected vehicles, or physical infrastructure for smart cities.
How will auto companies use data to meet the demands of the future?
Asia Pacific enterprises need to look beyond just collecting data.
As companies embrace business differentiating innovations, such as GPU databases, they can simultaneously meet the key requirements of GDPR.
Technologies built for the past are not going to keep up with solving these emerging extreme data problems.
Unlike societies, economies, and businesses that existed in the prior Industrial Revolutions, however, we need to be proactive in how we mitigate and minimize the impact of these transformational changes on those people who would be disadvantaged by them.
As we shift into the Extreme Data Economy, the energy sector is facing new challenges
As an enterprise product executive with a demonstrated history of bringing innovative products to market across a variety of sectors, Irina comes to Kinetica from Riverbed Technology.
IMPACT 50 LIST (in order of the most impactful)
Kinetica CTO Nima Negahban made datanami's People to Watch in 2018 list!
In essence, the value of IoT is in building more intimate digital relationships by correlating data across users, devices, and things, and translating it into instant insight.
As entire industries announce digital transformation initiatives leveraging big data, many companies are working behind the scenes to enable these success stories
How can your organization optimize its information flow? Check out our CMO Daniel Raskin's segment starting at 12:30 in.
Kinetica’s CTO and Co–founder Nima Negahban offers some of his top technology predictions for 2018.
Using Extreme Analytics To Turn Telco Networks Into Customer Insight Channels In The Post-Big Data Era
Beyond the satellite networks, the telecommunications industry is taking fire from all angles.
Artificial intelligence (AI) may soon be ubiquitous in next-gen tech for real-time, replacing “human intel” for mundane tasks — but it needs monitoring.
There is more to a successful application of machine learning than data science
Despite rapid innovations in accelerated parallel computing and machine learning, many banks have yet to make the leap from the big data era into the Extreme Data Economy
I am passionate about aligning technology to solving the business problems that matter. To me, this is about turning real-time analytics from a science experiment into technology businesses can immediately put to use and understand.
We have moved beyond the big data era into the Extreme Data Economy. In this new world, businesses need to translate massive volumes of complex data at unparalleled speed into omnichannel insight, with streaming data analysis, visual foresight and streamlined machine learning.
Kinetica, provider of the instant insight engine for the Extreme Data Economy, today announced its formal launch into the Australian market.
The data-powered business operates at hyper scale, with hyper complexity and at hyper speed.
insideBIGDATA Special Report: Reinventing the Retail Industry through Machine and Deep Learning (Part 3)
As data from the Internet of Things (IoT) increased, businesses started dealing with the challenge of analyzing streaming data in real time. At present, GPUs offer the most cost-effective solution for large amounts of data being streamed in real time
AI now pervades the world of big business, and is kickstarting new business models, and whole new ways of getting jobs done. How can your organization benefit?
With a GPU-accelerated database, you can use both simple and complex machine learning and deep learning algorithms on one platform.
Negahban predicts 2018 will see an increase in investments in AI life cycle management, and technologies that house the data and supervise the process will mature.
Yesterday’s technologies won’t solve today’s problems. We seem to be learning this over and over again. While that is the bad news, the good news is that there are also brilliant minds that create new technologies to solve those problems.
To integrate data-driven AI into operationalized pipelines, organizations will need a single platform capable of streamlining, automating and managing the entire Machine Learning and Deep Learning lifecycles.