• Home
  • About Us
  • Contact Us
  • Privacy Policy
  • Special Offers
Business Intelligence Info
  • Business Intelligence
    • BI News and Info
    • Big Data
    • Mobile and Cloud
    • Self-Service BI
  • CRM
    • CRM News and Info
    • InfusionSoft
    • Microsoft Dynamics CRM
    • NetSuite
    • OnContact
    • Salesforce
    • Workbooks
  • Data Mining
    • Pentaho
    • Sisense
    • Tableau
    • TIBCO Spotfire
  • Data Warehousing
    • DWH News and Info
    • IBM DB2
    • Microsoft SQL Server
    • Oracle
    • Teradata
  • Predictive Analytics
    • FICO
    • KNIME
    • Mathematica
    • Matlab
    • Minitab
    • RapidMiner
    • Revolution
    • SAP
    • SAS/SPSS
  • Humor

Tag Archives: Over

Fastest way to do repeated subsample/Intersection calls over large set of vectors

April 3, 2021   BI News and Info

 Fastest way to do repeated subsample/Intersection calls over large set of vectors

Let’s block ads! (Why?)

Recent Questions – Mathematica Stack Exchange

Read More

Contest for control over the semantic layer for analytics begins in earnest

January 25, 2021   Big Data
 Contest for control over the semantic layer for analytics begins in earnest

How open banking is driving huge innovation

Learn how fintechs and forward-thinking FIs are accelerating personalized financial products through data-rich APIs.

Register Now


A battle for control over how data is processed by analytics applications is starting to emerge in the cloud. Providers of data warehouses such as Snowflake, Amazon Web Services (AWS), and Microsoft are aggregating massive amounts of data. Naturally, providers of analytics and business intelligence (BI) applications are treating data warehouses as another source from which to pull data.

Snowflake, however, is making a case for processing analytics on its data warehouse. For example, in addition to processing data locally within its in-memory server, Alteryx is now allowing end users to process data directly on the Snowflake cloud.

At the same time, however, startups that enable end users to process data using a semantic layer that spans multiple clouds are emerging. A case in point is Kyligence, a provider of an analytics platform for Big Data based on open source Apache Kylin software.

Given the total cost of data warehouse platforms in the cloud, providers of these services are anxious to surface value that goes beyond merely being a repository for data, said Mike Leone, an industry analyst with Enterprise Strategy Group (ESG). “They want the data warehouse to be the entry point for other services,” said Leone. “Otherwise, the data warehouse is too expensive.”

That effort is drawing support from vendors, such as Alteryx, as the amount of data in a Snowflake repository increases.

However, Alteryx remains committed to a hybrid cloud strategy, said Sharmila Mulligan, the company’s chief marketing officer. Most organizations will have data that resides both in multiple clouds and on-premises for years to come. The idea that all of an organization’s data will reside in a single data warehouse in the cloud is fanciful, she said. “Data is always going to exist in multiple platforms,” said Mulligan. “Most organizations are going to wind up with multiple data warehouses.”

Similarly, Kyligence is trying to provide an analytics platform that spans multiple platforms. It pulls data from multiple platforms to create an online analytical processing (OLAP) database that provides end users with a familiar construct for analyzing data, said Li Kang, head of North America for Kyligence.

The company thus far has raised $ 48 million in pursuit of that goal. Redpoint Ventures, Cisco, China Broadband Capital, Shunwei Capital, Eight Roads Ventures, and Coatue Management are all investors. Kyligence counts UBS, Costa, Appzen, McDonald’s, YUM, L’OREAL, Porsche, Xactly, China Merchants Bank, and China Construction Bank among its customers.

Yesterday, Kyligence announced it’s making an enterprise edition of Apache Kylin ,dubbed Kyligence Cloud 4, available on the AWS and Microsoft Azure clouds where it can pull data from not just Snowflake, but also object-based storage repositories. Previously, the enterprise edition of the platform was available only for on-premises platforms.

That capability is critical, because over time the primary platform organizations will opt to store data on will change, noted Kang. “The center of data gravity tends to shift,” said Kang.

Kyligence Cloud, in effect, is an example of the additional semantic layer for processing and analyzing that is starting to emerge in hybrid cloud computing environments, said Kevin Petrie, vice president of research for the Eckerson Group. “By analyzing SQL queries and automatically building OLAP indices to pre-compute results, they can help enterprises offload a lot of the queries that would otherwise hit the data warehouse,” he said.

Regardless of the path forward, it’s not clear that data warehouses will emerge as data processing powerhouses. In many cases, they are just the latest incarnation of a data lake. The challenge IT organizations face now is making sure this latest iteration of a data lake doesn’t turn into yet another swamp.

VentureBeat

VentureBeat’s mission is to be a digital town square for technical decision-makers to gain knowledge about transformative technology and transact.

Our site delivers essential information on data technologies and strategies to guide you as you lead your organizations. We invite you to become a member of our community, to access:

  • up-to-date information on the subjects of interest to you
  • our newsletters
  • gated thought-leader content and discounted access to our prized events, such as Transform
  • networking features, and more

Become a member

Let’s block ads! (Why?)

Big Data – VentureBeat

Read More

Visualize 5 Cool Insights on Holiday Tree Trends Over Time

December 31, 2020   TIBCO Spotfire
TIBCOSpotfire ChristmasTree scaled e1608573759606 696x365 Visualize 5 Cool Insights on Holiday Tree Trends Over Time

Reading Time: 3 minutes

Did you know Thomas Edison’s assistants proposed putting electric lights on Christmas trees? There’s a long and rich history surrounding holiday trees, in America and around the world. According to the History Channel, symbolic traditions involving evergreen trees in winter began in ancient Egypt and Rome and continue to take on new meaning today. 

New Holiday Traditions: Annual Analytics

Here at TIBCO, we’ve started our own holiday tradition involving the classic festive trees: using our data visualization software to understand trends in holiday tree data. Last year, we shared our analysis and “treemap” visualization (quite literally a treemap of trees) via TIBCO Spotfire®. This year, we dived even deeper into the data, using the new Spotfire Mods functionality to design custom apps for greater interactivity. Here’s what we found:

  • Top Tree Producing States: All 50 states contribute to the holiday tree industry, but our analysis shows the greatest production occurs in Oregon, North Carolina, Michigan, and Pennsylvania. Also interesting is that while Oregon and North Carolina are top producers overall, states like Ohio and Michigan definitely over-index for total tree producing counties as a percentage of their total land area. 
 Visualize 5 Cool Insights on Holiday Tree Trends Over Time
Immersive, interactive exploration of a bubble “tree-map” visualization Mod alongside county-level Spotfire geoanalytics  [*source: USDA census data]    
  • Artificial vs. Real Tree Sales: As you can see below, artificial tree sales have been on the rise over the last decade, with 162 percent growth between 2004 and 2018. Artificial trees are taking over. Actually, 81 percent of the trees on display, whether in storefronts, businesses, or homes, in 2019 were of the artificial variety. But what does that mean for the global economy when China produces 80 percent of artificial trees worldwide and given that artificial trees cannot be recycled like real trees?
 Visualize 5 Cool Insights on Holiday Tree Trends Over Time
Tree sales volume over time in this area chart visualization Mod in Spotfire [*source: National Christmas Tree Association] 
  • Rising Average Price of Real Trees: According to an article in the Hustle, “During the recession in 2008, ailing farmers planted too few trees. As a result, prices have been much higher since 2016.” The article also cites the National Christmas Tree Association as stating that the average retail price for a real tree in 2019 was $ 75. Obviously, this is a huge market, but one that continues to shift with economic and social changes—which makes us wonder just how different our analysis next year will look.
  • Consumer Demand Lower in 2019: In the area chart visualization above, we see that sales for natural trees still account for a larger share of the market. However, the artificial tree category set new high marks for sales in each year progressively from 2016 to 2018. Why could this be? One hypothesis might be that as Baby Boomers retire as “empty-nesters” and downsize their homes, they are buying fewer trees, but let us know your thoughts on this surprising find. 
  • The More the Merrier? Multiple Trees: According to a survey by the American Christmas Tree Association, the number of households in the United States that display more than one Christmas tree has grown by 10 percent from 2014 to 2019. In 2019, approximately 16 percent of American households display multiple trees. But will this trend continue or, as with the overall tree sales, will the number of trees per household decrease in the coming years?

We’ve started our own holiday tradition involving the classic festive trees: using our data visualization software to understand trends in holiday tree data. Click To Tweet

A New Tradition: Immersive Yourself in Custom Analytics Applications 

But this is just one festive story you could tell around data trends. What about shopping trends this year, will there be an increase in small business online sales? What will be the top gifted items in 2020? 
You tell us! Join our tradition, and read our whitepaper to learn how the immersive qualities of Hyperconverged Analytics will create new value for your business. For a closer look at all of “What’s New in Spotfire®” including visualization Mods, watch our 20-minute intro webinar on demand. 

Previous article20 for 2020: Looking Back on a Year of Blogging

Shannon Peifer is a Marketing Content Specialist at TIBCO Software in Denver, CO. She graduated from the University of Texas at Austin in 2018 with a double major in marketing and English honors, and loves writing engaging content related to technology. Shannon grew up overseas, and loves to explore new places. When she’s not writing, you can find her swimming laps at the pool, gulping down iced lattes at local coffee shops, or scouring the shelves at the bookstore.

Let’s block ads! (Why?)

The TIBCO Blog

Read More

Google AI ethics co-lead Timnit Gebru says she was fired over an email

December 3, 2020   Big Data
 Google AI ethics co lead Timnit Gebru says she was fired over an email

When it comes to customer expectations, the pandemic has changed everything

Learn how to accelerate customer service, optimize costs, and improve self-service in a digital-first world.

Register here

Timnit Gebru, one of the best-known AI researchers today and co-lead of an AI ethics team at Google, no longer works at the company. Details are still being gathered, but according to Gebru, she was fired Wednesday for sending an email to “non-management employees that is inconsistent with the expectations of a Google manager.” She said Google AI employees who report to her were emailed and told that she accepted her resignation when she did not offer her resignation. VentureBeat reached out to Gebru, a Google spokesperson, and Google AI chief Jeff Dean for comment. This story will be updated if we hear back.

I was fired by @JeffDean for my email to Brain women and Allies. My corp account has been cutoff. So I’ve been immediately fired icon smile Google AI ethics co lead Timnit Gebru says she was fired over an email

— Timnit Gebru (@timnitGebru) December 3, 2020

In a tweet published days before leaving Google, Gebru questioned whether there’s regulation that protects people from divulging whistleblower law protection for members of the AI ethics community.

Gebru left Google the same day that the National Labor Review Board (NLRB) filed complaints against Google that found that the company spied on and illegally fired two employees involved in labor organizing.

today the nlrb said i was illegally fired. it took a year. i hope they acknowledge what is happening to Timnit sooner. #ISupportTimnit #BelieveBlackWomenhttps://t.co/Qkvd4hFrZE

— kathryn spiers (@computerfemme) December 3, 2020

Tawana Petty is a data justice and privacy advocate in Detroit who this week was named national organizing director of Data for Black Lives. This morning she gave a talk about the legacy of surveillance of Black communities with tech like facial recognition and the toxicity of white supremacy on people’s lives. She dedicated her keynote talk at the 100 Brilliant Women in AI Ethics conference to Timnit Gebru.

“She was terminated for what we all aspire to do and be,” Petty said.

Mia Shah-Dand, who organized the conference and previously worked at Google, called Gebru’s dismissal a reflection of toxic culture in tech and a sign that women, particularly Black women, need support.

I thought this was a joke because it seemed ridiculous that anyone would fire @timnitGebru given her expertise, her skills, her influence. This is one of the many times when I think there is just no hope for the tech industry. https://t.co/2Px7nkObke

— Ellen K. Pao (@ekp) December 3, 2020

Timnit Gebru is known for some of the most influential work in algorithmic fairness research and combating algorithmic bias with the potential to automate oppression. Gebru is a cofounder of the Fairness, Accountability, and Transparency (FAccT) conference and Black in AI, a group that hosts community gatherings and mentors young people of African descent. Black in AI holds its annual workshop Monday at NeurIPS, the largest AI research conference in the world.

Before coming to Google, Gebru joined Algorithmic Justice League founder Joy Buolamwini and created the Gender Shades project to assess the performance of facial recognition systems from major vendors like IBM and Microsoft. As part of that work, a peer-reviewed paper concluded that facial recognition tends to work best on white men and worst for women with a dark skin tone. That research and subsequent work by Buolamwini and Deborah Raji in 2019 have been highly influential among lawmakers deciding how to regulate the technology and people’s attitudes about the threat posed by algorithmic bias.

I gave Google the benefit of the doubt re: AI ethics and fairness entirely because of the existence of Timnit’s team and the work they do there, knowing she and others are outspoken advocates and activists.

Now that she’s been fired, I’d argue Google no longer deserves it. https://t.co/sazZvz2iDS

— Cathy O’Neil (@mathbabedotorg) December 3, 2020

While working at Microsoft Research, she was lead author of “Datasheets for Datasets,” a paper that recommends including a set of standard information with datasets in order to provide data scientists with context before they decide to use that data for training an AI model. “Datasheets for Datasets” would later act as motivation for the creation of model cards.

As a Google employee, Gebru joined Mitchell, Raji, and others in writing a paper in 2019 about model cards, a framework for providing benchmark performance information about a model for machine learning practitioners to evaluate before using an AI model. Google Cloud began providing model cards for some of its AI last year, and this summer introduced the Model Card Toolkit for developers to make their own model cards.

This summer, Gebru and her former colleague Emily Denton led a tutorial about fairness and ethics in computer vision at the Computer Vision and Pattern Recognition (CVPR) which organizers called “required viewing for us all.” Shortly after that she got into a public spat with Facebook director of AI research Yann LeCun about AI bias, which turned out to be a teachable moment for LeCun, who won the Turing Award in 2019 for his work on deep learning.

Member of the AI community and others have at times have referred to Gebru as someone actively trying to save the world. Earlier this year, Gebru led a was included in the book “Good Night Stories for Rebel Girls: 100 Immigrant Women Who Changed the World,” a book that was released in October.

Let’s block ads! (Why?)

Big Data – VentureBeat

Read More

Autonomous vehicle startup Pony.ai raises $267 million at an over $5.3 billion valuation

November 6, 2020   Big Data

Maintain your employer brand in a pandemic

Read the VentureBeat Jobs guide to employer branding

Download eBook

In a sign that enthusiasm for driverless cars hasn’t waned during the pandemic, Pony.ai today announced $ 267 million in new funding. The startup has offices in Guangzhou, China and Fremont, California and has now raised over $ 1 billion at a valuation north of $ 5.3 billion (up from $ 3 billion as of February 2020).

Some experts predict the pandemic will hasten the adoption of autonomous transportation technologies. Despite needing disinfection, driverless cars can potentially minimize the risk of spreading disease. But surveys are mixed, with one from Partners for Automated Vehicle Education showing nearly three in four Americans believe autonomous cars aren’t ready for prime time. Unsurprisingly, Motional disagrees with this assertion, claiming one-fifth of respondents to its Consumer Mobility Report are “more interested” in autonomous vehicles than they were before the pandemic.

 Autonomous vehicle startup Pony.ai raises $267 million at an over $5.3 billion valuation

Former Baidu chief architect James Peng cofounded Pony.ai in 2016 with Tiancheng Lou, who worked at Google X’s autonomous car project before it was spun off into Waymo. The pair aims to build level 4 autonomous cars — able to operate without human oversight under select conditions, as defined by the Society of Automotive Engineers — for “predictable” environments, such as industrial parks, college campuses, and small towns, with a tentative deployment window of several years from now.

Pony’s full-stack hardware platform, PonyAlpha, leverages lidars, radars, and cameras to keep tabs on obstacles up to 200 meters from its self-driving cars. PonyAlpha is the foundation for the company’s fully autonomous trucks and freight delivery solution, which commenced testing in April 2019 and is deployed in test cars within the city limits of Fremont and Beijing (in addition to Guangzhou).

Pony.ai is one of the few companies to have secured an autonomous vehicle testing license in Beijing. In California, it has obtained a robo-taxi operations permit from the California Public Utilities Commission. The only other companies to have secured such a license in California are AutoX, Waymo, and Zoox.

Last October, Pony.ai partnered with Via and Hyundai to launch BotRide, Pony.ai’s second public robo-taxi service after a pilot program (PonyPilot) in Nansha, China. BotRide allowed riders and carpoolers to hail autonomous Hyundai Kona electric SUVs through apps developed with Via, sourcing from a fleet of 10 cars with human safety drivers behind the wheel.

 Autonomous vehicle startup Pony.ai raises $267 million at an over $5.3 billion valuation

In August, Pony.ai inked an agreement with Bosch to “explore the future of automotive maintenance and repair for autonomous fleets.” Pony.ai and Bosch’s Automotive Aftermarket division in North America plan to develop and test fleet maintenance solutions for commercial robo-taxi programs. Pony.ai says it began piloting a maintenance program with Bosch in the San Francisco Bay Area in early July.

Among other potential advantages, autonomous driving promises the continuous operation of fleets and reduction of downtime. According to a 2017 McKinsey report, robo-taxis could reduce a fleet operator’s total cost of ownership by 30% to 50% compared with private-vehicle ownership and by about 70% compared to shared mobility, significantly disrupting the market. But robo-taxis will need vastly different maintenance infrastructure than cars, in part because they might lack regular monitoring; have only minutes between passengers; and sport expensive, sensitive, and unconventional parts like lidar sensors.

Pony.ai has competition in Daimler, which in summer 2018 obtained a permit from the Chinese government that allows it to test self-driving cars powered by Baidu’s Apollo platform on public roads in Beijing. And startup Optimus Ride built out a small driverless shuttle fleet in Brooklyn. Waymo, which has racked up more than 20 million real-world miles in over 25 cities across the U.S. and billions of simulated miles, in November 2018 became the first company to obtain a driverless car testing permit from the California Department of Motor Vehicles (DMV). Rivals include Tesla, Aptiv, May Mobility, Cruise, Aurora, Argo AI, Pronto.ai, and Nuro.

Fortunately for Pony.ai, it has partnerships with Chinese state-owned auto group FAW and GAC Group (a Guangzhou-based automobile maker) to develop level 4 robo-taxi vehicles. It also has a joint collaboration with On Semiconductor to prototype image sensing and processing technologies for machine vision. And Pony.ai has driven over 1.5 million autonomous kilometers (or about 932,056 miles) as of year-end 2019, putting it within striking distance of Yandex (2 million miles) and Baidu (1.8 million miles).

Previous and existing investors in Pony.ai include video game publisher Beijing Kunlun Wanwei, Sequoia Capital China, IDG Capital, and Legend Capital. The Ontario Teachers’ Pension Plan Board’s Teachers’ Innovation Platform led this latest round, with participation from Fidelity China Special Situations PLC, 5Y Capital, ClearVue Partners, Eight Roads, and others.

Sign up for Funding Weekly to start your week with VB’s top funding stories.

Let’s block ads! (Why?)

Big Data – VentureBeat

Read More

Why Hasn’t CRM Taken Over the World?

October 9, 2020   CRM News and Info

Throughout the early fall, analysts have been treated to a continuous stream of announcements from the CRM community, especially Salesforce and Oracle. New product availability belies the facts on the ground of an economy hobbled by a pandemic. It’s a gusher of good technology intended for a market eager to snap it up. That said, I am not sure about the market and we might be looking at a technology glut.

Glut is a strange word in software since there’s no inventory to back up as you’d see in a more conventional glut. Over the summer gas process were very low because producers kept pumping in the face of declining demand which created a glut. Software is different, especially in the cloud era. When demand happens it’s a simple transaction and users can begin almost immediately to use the technology. But that doesn’t mean you can’t have a glut.

My research this year establishes a disconnect between the wonderful features and functions of the new technologies and the realities of how companies use them — or not. In surveys of over one thousand end users from as many companies of all sizes, including multi-billion-dollar ones, the evidence shows that this technology is not reaching users.

They complain of stand-alone systems that aren’t integrated and of running as many as eight apps at once trying to do their jobs. People understandably run out of time in a day too. They work long hours, do business from their phones at the gym, their children’s school activities, and even in the bathroom.

The old hypothesis explaining this lack of adoption was that software was too costly and took too much time to install or maintain. Back in the day that was true, but no more. Cloud computing is easy to install and use, and cheap and while we’re at it, and vendors refresh apps with new features and functions multiple times per year. That’s a far cry from the annual upgrade season we saw twenty years ago.

So What’s Going On?

You might be tempted to blame economic conditions for slack demand if it exists, but that’s not it. My surveys straddle COVID’s before and after. In truth, for the two plus decades that I’ve been following CRM, there’s always been adoption reluctance emanating from the front office. Rather than accepting CRM’s different approach to doing business, many people still resist it, preferring to go with their gut or stick with manual systems, because updating CRM is tedious.

Many businesses have bought into CRM, of course. It isn’t an 80-billion-dollar industry for nothing. But for many years we’ve seen that only about a quarter of organizations use CRM appropriately. Others use it for simple record keeping, or barely use it at all. A great tell for this is that in one of my studies, CRM ranked only fourth in importance as a tool people use daily. Email ranked higher. Email.

This is important to everyone because the first decades of CRM were largely about gathering and consolidating data that people could use in their customer-facing jobs. But today, a lot of those jobs have been automated away. When was the last time you went to a website or made a call for support and interacted with a person? You could, but first you needed to get through a very good self-service system that likely solved your problem sans human.

We’ve turned a corner in CRM. Two decades ago, you could put off adoption by saying the stuff doesn’t work or it doesn’t fit my oh-so-unique business. Not so much anymore.

This fall companies like Salesforce are introducing advanced vertical industry specific solutions while Oracle continues to refine its platform, analytics and infrastructure to do much the same.

All of this is done in an effort to boost the prospects of what’s been called the digital disruption, but is increasingly becoming just business as usual, which brings us to the glut. Currently available CRM systems might now outstrip the abilities of customers to adopt them.

Training Is Essential to Progress

It’s tempting to say that customers just need to get down to work, but that ignores a pressing reality. If my data is right, the people who need CRM are already under water. They’re working too hard and spending more than the eight hours a day that they’re paid for. So there’s scarcely any time to take on something new. That’s partly why my studies indicate relative complacency with the cobbled together systems they’re using — at least they can do their jobs, make their quotas and go home.

Learning something new at work, no matter how good it is, can be a daunting task and one that needs to be supported by organizations that have used CRM to reduce their overhead. Learning might mean bringing on a few more people to spread the work around and make feasible learning something new.

This should surprise exactly no one, though business has often not been good at this kind of transition. In the 1970s and ’80s car makers went through a similar turning point. It was a time when they were converting from mostly rear-wheel drive cars to front wheel-drive. At the same time, they were obsessed with quality control, reimagining the manufacturing process, and introducing robots. They were also fighting enhanced foreign competition for the first time.

There’s a reason for new technology adoption reluctance. During that era U.S. auto makers lost about half of their market share.

That’s about where we are in CRM today. Some companies are adopting digital disruption strategies early, while others haven’t kept up. The big difference today however is that the big vendors are taking steps to protect their customers from the downside risks. They’re spinning up online training functions and bringing in expert partners to help.

Ultimately, it’ll take additional resources from both vendors and customers to bring us into the digital CRM era. So, as I look at all of the new technology available this fall, I smile at vendor creativity and I hope that ingenuity extends to new approaches to implementation, training, and even financing.
end enn Why Hasnt CRM Taken Over the World?


Denis%20Pombriant Why Hasnt CRM Taken Over the World?
Denis Pombriant is a well-known CRM industry analyst, strategist, writer and speaker. His new book, You Can’t Buy Customer Loyalty, But You Can Earn It, is now available on Amazon. His 2015 book, Solve for the Customer, is also available there.
Email Denis.

Let’s block ads! (Why?)

CRM Buyer

Read More

Advocacy groups raise concerns over Google’s $2.1 billion Fitbit bid

July 4, 2020   Big Data
 Advocacy groups raise concerns over Google’s $2.1 billion Fitbit bid

(Reuters) — Twenty advocacy groups from the United States, Europe, Latin America, and elsewhere signed a statement Wednesday urging regulators to be wary of Google’s $ 2.1 billion bid for fitness tracker company Fitbit because of privacy and competition concerns.

The 20 organizations — which include the U.S.-based Public Citizen, Access Now from Europe and the Brazilian Institute of Consumer Defense — argued that the deal would expand Alphabet subsidiary Google’s already considerable clout in digital markets.

Acquiring Fitbit would give Google such intimate information about users as how many steps they take daily, the quality of their sleep, and their heart rates.

“Past experience shows that regulators must be very wary of any promises made by merging parties about restricting the use of the acquisition target’s data. Regulators must assume that Google will in practice utilize the entirety of Fitbit’s currently independent unique, highly sensitive data set in combination with its own,” the groups said.

VB Transform 2020 Online – July 15-17. Join leading AI executives: Register for the free livestream.

Australian and Canadian groups were among the signatories.

A Google spokesperson said the tech wearables space was crowded.

“This deal is about devices, not data,” she said. “We believe the combination of Google’s and Fitbit’s hardware efforts will increase competition in the sector.”

Google announced the deal in November to take on competitors in the crowded market for fitness trackers and smart watches. Fitbit’s market share has been threatened by deep-pocketed companies like Apple and Samsung.

Australia’s competition authority said this month that it may have concerns about the deal and would make a final decision in August.

EU antitrust regulators will decide by July 20 whether to clear the deal with or without concessions or open a longer investigation.

In Washington, Google is under antitrust investigation by the Justice Department, a congressional committee, and dozens of states for allegedly using its massive market power to harm smaller competitors.

(Reporting by Diane Bartz, editing by Lisa Shumaker.)

Let’s block ads! (Why?)

Big Data – VentureBeat

Read More

Why Millennials Prefer the Security of Microsoft Dynamics Over Other CRM Systems

May 16, 2020   CRM News and Info

With so many privacy scandals making headlines, the current workforce well understands the importance of security. Choosing a system that provides this protection for employees and customers is essential for Millennials, who make up the majority of modern employees.

Microsoft Dynamics is a leader in global security. Microsoft delivers layered security in all applications to allow workers to do their best work anywhere with full confidence. Consider briefly how Microsoft Dynamics provides the security needed for any company:

Security anywhere

Microsoft Dynamics provides physical and virtual security. These include access control, encryption, and authentication. This helps protect data on all devices whether it be mobile phones, tablets, or computers. Role-based security defines access to system data no matter where they are working.

Intelligent security

As security risks continue to rapidly grow, modern workers not only want but expect the systems they work with to be protected. Microsoft Dynamics meets these expectations by using billions of data points globally to engineer techniques and apply intelligence to progressively improve security.

Protect customer data

Employees today want to be confident that the data they collect from customers is secure and fully protected. Microsoft Dynamics keeps this data safe by preventing the disclosure of all personal and financial information. This makes it easy to maintain customer loyalty and comply with industry regulations.

Thomas Berndorfer, CEO of Connecting Software trusts Microsoft Dynamics to be completely secure in handling his company’s sensitive information. He says: “Dynamics 365 provides a robust data security model, and add-on products ensure data protection between D365 and other Microsoft apps.”

Would you like to see how they use Microsoft Dynamics’ security could benefit your business?

Read this and 18 other reasons why Millennials prefer Microsoft Dynamics in the workspace by downloading the full eBook “21 Reasons Millennials Prefer Microsoft Dynamics” at www.crmsoftwareblog.com/millennials to read 17 more reasons why Millennials prefer Microsoft Dynamics in the workspace.

Find a Microsoft Dynamics 365 Partner

By CRM Software Blog Writer, www.crmsoftwareblog.com

Let’s block ads! (Why?)

CRM Software Blog | Dynamics 365

Read More

77 autonomous vehicles drove over 500,000 miles across Beijing in 2019

March 3, 2020   Big Data

Hot on the heels of the California Department of Motor Vehicle’s annual autonomous vehicle disengagement report, Beijing’s Innovation Center for Mobility Intelligent (BICMI), the city’s service agency vehicle tests, published its 2019 survey of self-driving vehicles testing on local roads. Beyond Pittsburgh, Pennsylvania, Beijing is one of the few cities globally that mandates autonomous car companies disclose the miles they’ve driven, as well as the size of their vehicle fleets and the disengagements — or autonomous system failures — they experienced.

A total of 77 autonomous vehicles from 13 China-based companies — including Baidu, Nio, Beijing New Energy, Daimler, Pony.ai, Tencent, Didi, Audi, Chongqing Jinkang, NavInfo, Toyota, and Beijing Sankuai — covered 1.04 million kilometers (~646,226 miles) on Beijing roads during 2019, according to the BICMI. That’s up from the 153,600 kilometers (~95,442.6 miles) 8 firms drove in 2018.

 77 autonomous vehicles drove over 500,000 miles across Beijing in 2019

Above: The mileage numbers are in kilometers and truncated. Multiply by 10,000 to get the mileage in each cell.

Image Credit: Baidu

Baidu’s 52 cars covered a total of 754,000 kilometers (~468,513 miles), putting the tech giant in the lead with over five times the number of miles it notched in 2018 (140,000 kilometers; 86,991 miles). As for Pony.ai, its fleet of 5 cars drove 111,200 kilometers (~69,096 miles), substantially improving upon 2018’s 10,132 kilometers (6,296 miles). And Toyota’s 4 cars ranked third with 11,100 kilometers (~6,897 miles).

The BICMI doesn’t break out disengagement numbers by company or vehicle, but it said that 86% in 2019 resulted from human takeovers — i.e., drivers tinkering with data-recording equipment, changes in planned routes, or “personal reasons” (like bathroom breaks). The remaining 14% of disengagements were attributable to some form of mechanical or software systems failure.

Of course, whether disengagements communicate anything meaningful remains the subject of debate. In a conversation with VentureBeat, Dmitry Polishchuk, the head of Russian tech giant Yandex’s autonomous car project, noted that Yandex hasn’t released a disengagement report to date for this reason. “We have kind of been waiting for some sort of industry standard,” he said. “Self-driving companies aren’t following the exact same protocols for things. [For example, there might be a] disengagement because there’s something blocking the right lane or a car in the right lane, and [the safety driver realizes] as a human that [this object or car] isn’t going to move.”

 77 autonomous vehicles drove over 500,000 miles across Beijing in 2019

The BICMI’s report is a part of China’s strategy to bolster driverless technologies development in the region, which was outlined in a recent whitepaper by the National Development and Reform Commission, the Ministry of Industry and Information Technology, and nine other “ministerial-level” authorities. As early as 2025, China intends to codify guidelines around infrastructure, regulatory supervision, and safety that enable companies to “scale production of vehicles capable of conditional autonomous driving” and to “[commercialize] … highly autonomous vehicles in certain circumstances.”

As of the end of December, Beijing has allowed 151 roads spanning 503.68 kilometers (~312 miles) in length to be used for autonomous vehicle tests, supplementing a test area about 40 square kilometers (~24 miles) in size within the city limits. China has designated five levels for self-driving test permits ranging from T1 to T5, which are similar (but not necessarily analogous) to the automation levels issued by the Society of Automotive Engineers.

The Beijing Municipal Commission of Transport allocated its first batch of T4 autonomous test permits to pack leader Baidu last July. The company noted at the time that the T4 — China’s highest-level permit — is an open-road test license, enabling it to deploy driverless vehicles on urban roads, tunnels, school zones, and elsewhere.

Baidu announced in late 2019 that it had secured 40 licenses to test driverless cars carrying passengers on designated roads on Beijing, making it one of the first to do so in the Chinese capital. It seeks to gain the upper hand over well-financed rivals like Tencent, Alibaba, and Pony.ai; in April, Alibaba confirmed that it has been conducting self-driving car tests with the goal of achieving Level 4 autonomous capability and said that it’s looking to hire as many as 50 engineers for its AI research lab. In May, Tencent secured a license from the Chinese government to begin testing autonomous cars in Shenzhen, China. And just last week, Pony.ai raised $ 462 million in venture capital at a $ 3 billion valuation.

Baidu and the competition are racing toward a veritable goldmine of a market. Autonomous vehicles and mobility services in China are expected to be worth more than $ 500 billion by 2030, according to a McKinsey report, when as many as 8 million self-driving cars hit public roads.

Let’s block ads! (Why?)

Big Data – VentureBeat

Read More

Fall in Love with Your Data All Over Again

February 14, 2020   TIBCO Spotfire
TIBCO LoveYourData 696x365 Fall in Love with Your Data All Over Again

Reading Time: 2 minutes

Show your data some extra love this Valentine’s Day. Recommit to solving your most complex business problems with data and develop an action plan to operationalize your data across your organization. 

In this blog, find out why TIBCO is the one for you—from unifying intelligently for better access, trust, and control, to connecting any application, device, or data source seamlessly, to predicting confidently with real-time data-driven intelligence.

The assets below are part of the Love Your Data series, taking you through the comprehensive TIBCO ® Connected Intelligence platform that can help you fall in love with your data all over again. Check out the following helpful resources of this Valentine’s week series:

Unified in Love 

Everyone today loves data, but not everyone is making the most of it. Only organizations that have unified their data intelligently can easily access, govern, and share it to deliver the greatest value. This Valentine’s day make sure not only your heart is in the right place, but so is your data. TIBCO’s data management solutions support 360-degree views of anything, both relationships in the master data and transactional details. 

This whitepaper can help you gain a holistic view of all the information in your organization and remind you of why you fell in love with what you’re doing in the first place. 

My Heart Belongs to Streaming BI 

Data is at the heart of every business today. Therefore, data analytics can often feel like monitoring a pulse, tracking where the business is and where it could be going in the future. If you’re making decisions based only on historical data, you’re missing the real-time critical information (vital signs) needed to make faster, smarter decisions. You can’t treat current problems with old data. 

Open your heart to TIBCO’s guide to streaming business intelligence (BI), diagnose issues in real time, and quickly outpace competitors. 

Cupid’s Connected Cloud 

While Cupid is flying the skies helping singles meet their mate, we’re hard at work making a different kind of connection. Watch this webinar to learn how the TIBCO Connected Intelligence platform can connect your enterprise’s disparate systems, allowing you to manage your entire digital business from one cloud-based interface. Now that’s what we call love.

I am a Sucker for Data 

Don’t let your love of analytics become overly complex. Too many companies today have an “It’s complicated” relationship with their data, struggling both to understand the massive amounts of data coming into the business each day and to take action on the insights they uncover for better, faster results. Simplify your data analytics initiatives by first understanding the different analytics approaches and the unique challenges each is designed to solve, as well as key considerations, requirements, and example use cases for each. 

Read this ebook to find the right type of analytics for you, perfectly matched based on your business needs. 

I only have APIs for You 

Your applications deserve to be together, and there’s no better way to do that than with a solid API-led integration strategy. Check out this eBook to learn how TIBCO’s API management solution will leave you—and your developers—on Cloud Nine! 

Lay the foundation for a strong relationship with your data using TIBCO. Learn more about how TIBCO allows you to connect to any data source, unify your data across your business, and predict future outcomes with confidence. And what better time of the year than Valentine’s Day to show your data just how much you love it?

Let’s block ads! (Why?)

The TIBCO Blog

Read More
« Older posts
  • Recent Posts

    • Accelerate Your Data Strategies and Investments to Stay Competitive in the Banking Sector
    • SQL Server Security – Fixed server and database roles
    • Teradata Named a Leader in Cloud Data Warehouse Evaluation by Independent Research Firm
    • Derivative of a norm
    • TODAY’S OPEN THREAD
  • Categories

  • Archives

    • April 2021
    • March 2021
    • February 2021
    • January 2021
    • December 2020
    • November 2020
    • October 2020
    • September 2020
    • August 2020
    • July 2020
    • June 2020
    • May 2020
    • April 2020
    • March 2020
    • February 2020
    • January 2020
    • December 2019
    • November 2019
    • October 2019
    • September 2019
    • August 2019
    • July 2019
    • June 2019
    • May 2019
    • April 2019
    • March 2019
    • February 2019
    • January 2019
    • December 2018
    • November 2018
    • October 2018
    • September 2018
    • August 2018
    • July 2018
    • June 2018
    • May 2018
    • April 2018
    • March 2018
    • February 2018
    • January 2018
    • December 2017
    • November 2017
    • October 2017
    • September 2017
    • August 2017
    • July 2017
    • June 2017
    • May 2017
    • April 2017
    • March 2017
    • February 2017
    • January 2017
    • December 2016
    • November 2016
    • October 2016
    • September 2016
    • August 2016
    • July 2016
    • June 2016
    • May 2016
    • April 2016
    • March 2016
    • February 2016
    • January 2016
    • December 2015
    • November 2015
    • October 2015
    • September 2015
    • August 2015
    • July 2015
    • June 2015
    • May 2015
    • April 2015
    • March 2015
    • February 2015
    • January 2015
    • December 2014
    • November 2014
© 2021 Business Intelligence Info
Power BI Training | G Com Solutions Limited