predictive analytics
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With an increasing number of enterprise systems, growing teams, a rising proliferation of the web and multiple digital initiatives, companies of all sizes are creating loads of data every day. This data contains excellent business insights and immense opportunities, but it has become impossible for companies to derive actionable insights from this data consistently due to its sheer volume.
According to Verified Market Research, the analytics-as-a-service (AaaS) market is expected to grow to $101.29 billion by 2026. Organizations that have not started on their analytics journey or are spending scarce data engineer resources to resolve issues with analytics implementations are not identifying actionable data insights. Through AaaS, managed services providers (MSPs) can help organizations get started on their analytics journey immediately without extravagant capital investment.
MSPs can take ownership of the company’s immediate data analytics needs, resolve ongoing challenges and integrate new data sources to manage dashboard visualizations, reporting and predictive modeling — enabling companies to make data-driven decisions every day.
AaaS could come bundled with multiple business-intelligence-related services. Primarily, the service includes (1) services for data warehouses; (2) services for visualizations and reports; and (3) services for predictive analytics, artificial intelligence (AI) and machine learning (ML). When a company partners with an MSP for analytics as a service, organizations are able to tap into business intelligence easily, instantly and at a lower cost of ownership than doing it in-house. This empowers the enterprise to focus on delivering better customer experiences, be unencumbered with decision-making and build data-driven strategies.
Organizations that have not started on their analytics journey or are spending scarce data engineer resources to resolve issues with analytics implementations are not identifying actionable data insights.
In today’s world, where customers value experiences over transactions, AaaS helps businesses dig deeper into their psyche and tap insights to build long-term winning strategies. It also enables enterprises to forecast and predict business trends by looking at their data and allows employees at every level to make informed decisions.
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You may not be familiar with Kaltura‘s name, but chances are you’ve used the company’s video platform at some point or another, given that it offers a variety of video services for enterprises, educational institutions and video-on-demand platforms, including HBO, Phillips, SAP, Stanford and others. Today, the company announced the launch of an advanced analytics platform for its enterprise and educational users.
This new platform, dubbed Kaltura Analytics for Admins, will provide its users with features like user-level reports. This may sound like a minor feature, because you probably don’t care about the exact details of a given user’s interactions with your video, but it will allow businesses to link this kind of behavior to other metrics. With this, you could measure the ROI of a given video by linking video watch time and sales, for example. This kind of granularity wasn’t possible with the company’s existing analytics systems. Companies and schools using the product will also get access to time-period comparisons to help admins identify trends, deeper technology and geolocation reports, as well as real-time analytics for live events.

“Video is a unique data type in that it has deep engagement indicators for measurement, both around video creation — what types of content are being created by whom, as well as around video consumption and engagement with content — what languages were selected for subtitles, what hot-spots were clicked upon in video,” said Michal Tsur, president and general manager of Enterprise and Learning at Kaltura. “Analytics is a very strategic area for our customers. Both for tech companies who are building on our VPaaS, as well as for large organizations and universities that use our video products for learning, communication, collaboration, knowledge management, marketing and sales.”
Tsur also tells me the company is looking at how to best use machine learning to give its customers even deeper insights into how people watch videos — and potentially even offer predictive analytics in the long run.
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Remember that future we were promised where our vehicle magically tells us that we’re about to break down? Or actually never does? Or that the pickup truck arrives before the driver even knows something is wrong? That future is arriving. But like many things, the practical reality is that this technology starts to arrive in the fleet management industry before it arrives for consumers.
The market for maintenance of fleets of buses and trucks is worth $200 billion in annual expenditure, so as you can imagine, it’s a juicy sector to get into. In Portugal, a team of entrepreneurs and scientists assembled to look into this and came up with a fascinating startup that is now attracting the attention of investors.
Today, Stratio is emerging from stealth to help OEMs, distributors and fleets benefit from AI-driven predictive intelligence.
The idea is to apply machine learning models that retrieve and analyze millions of data points per vehicle per day to vehicles both in development and on the road. It turns out that if you compare the real versus the expected behaviour of the actual vehicle components themselves, you can improve automated testing and predictive intelligence that can assess the vehicle’s condition. Then you can detect early anomalies and failures. This is exactly what Stratio does.
It does this by putting a sensor box-of-tricks under a vehicle, like a bus. This box connects with existing sensors in the vehicle using the existing API — something crucial for OEMs. Using proprietary machine learning, it can predict when something will break, days ahead of time. Most existing boxes like this only track location, not analytics.
Stratio also works with OEMs during the vehicle testing phase to identify issues and their root cause to get more reliable vehicles to market faster, lower the potential for warranty claim fraud costs and expand the after-sales revenues. It’s a triple whammy in cost savings.
Stratio has now attracted a $3.5 million VC round from London-based Crane VC, with participation from fellow London VC, LocalGlobe.
The round is one of the largest ever seed deals in Portugal and potentially the largest enterprise/deep tech first investment in the country.
It has a proprietary AI engine, Stratio CortexTM, and technology support from the European Space Agency. Ultimately the aim is to apply machine learning models and enable the so-called “zero downtime” future.
Rui Sales and Ricardo Margalho, co-founders of Stratio, say the idea for Stratio came to them when their bus broke down and they missed what could have been a career-changing meeting in New York: “Knowing that today’s existing vehicles produce a massive amount of data, we set out to build a machine learning product suite that analyses high-density vehicle data in real time to predict and prevent vehicles from breaking down.”
Stratio launched in 2017, after receiving technological support from the European Space Agency and earning recognition from the EU Commission.
Alongside the co-founders is Rune Prytz, a former Volvo Trucks research engineer in machine learning and big data, who now leads all of Stratio’s efforts in AI. Stratio now counts MAN, DAF Trucks and VECTIA as customers, among others.
Krishna Visvanathan, partner at Crane Venture Partners, commented, “Stratio Automotive is one of the most exciting companies in our portfolio of data-driven enterprise software businesses. It has the trifecta of a super product, a deep data moat coupled with AI expertise and great customer traction.”
So far, Stratio has attracted customers and operations in more than 10 key markets across Europe, the U.K., U.S., India and Singapore.
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Believe it or not, farmers in the U.S. have faced a labor shortage for years. U.S. citizens aren’t drawn to agriculture the way they were in previous generations. The labor trend has pushed farmers to automate some of the tasks done by agronomists and field workers in the past, using software, robotics and IoT devices like Arable’s. Read More
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Farmers know how hard it is to predict yield accurately. High-value crops like grapes or almonds prove particularly challenging. Farmers expect, and settle for, twenty to forty percent uncertainty with these crops. Vinsight founder and CEO, Megan Nunes, who grew up in the farming business, found that unacceptable. After almost a decade-long career in the satellite industry, she turned her… Read More
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Redwood City-based Glint has raised $27 million in a Series C round of venture funding for software that helps companies figure out how their teams are experiencing problems, or why and when solid employees may leave, undesirably. Glint replaces the traditional 360-review tools used by corporate HR teams and executives with short, anonymous surveys sent out once in a while to specific groups… Read More
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Artificial intelligence has an intellectual lineage stretching back to the greats of computer theory: Turing and, ultimately, Babbage, inventor of the calculating machine. What we now see in London, where leading teams such as DeepMind are working on machine learning, is the movement from the realm of computer science to practical uses and business cases. Read More
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While people believe that the tech world is in a bubble that is bound to pop soon, the investment climate for enterprise startups with good traction remains hot. In the latest development, InsideSales.com, a provider of predictive analytics services for salespeople to help them source and close deals, has raised another $60 million of funding. This latest round, which brings the total… Read More
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