Truthset raises $4.75M to help marketers score their data

Data, the cliché goes, is the new oil of the digital economy. But Truth{set} co-founder and CEO Scott McKinley wants to know: “Why does no one care about the quality of that fuel?”

That’s an issue McKinley saw in his seven years as an executive at Nielsen, where he said he realized that marketing data products are “all built on massive error.” As evidence, he pointed to recent studies showing that bad data leads marketers to waste 21 cents of every dollar, and that in many cases, consumer data is “similar to or even worse than what you’d get if you used random chance to create a target list.

McKinley argued, “You wouldn’t drive a car to a gas station where there’s no octane rating on the pump.” He created Truth{set} to provide that octane rating to marketers, and to “shine the light on that whole ecosystem.”

More specifically, the company scores the consumer data that marketers are buying on accuracy, on a scale between 0.00 and 1.00. To create these scores, Truth{set} checks the data against independent data sources, as well as first-party data and panels.

“In order for us to do this, we had to develop a perspective on what is truthful and what is not,” McKinley said. “And so instead of building our own data sets, we said, ‘Let’s be smarter than that, let’s verify everybody else’s data with these independent sources of truth.’ ”

Truthset screenshot

Image Credits: Truthset

In addition to coming out of stealth, Truth{set} is also announcing that it has raised $ 4.75 million in seed funding from startup studio super{set}, WTI, Ulu Ventures and strategic angel investors.

The company says it’s compatible with demand-side platforms, data management platforms and customer platforms. It also integrates with the leading data providers, including Facebook, LiveRamp and The Trade Desk.

McKinley added that the platform can even “suppress” consumer IDs that don’t meet a marketer’s standards, so that they’re not used in targeting.

Throughout our conversation, he emphasized the idea of independence, arguing that in order to provide trustworthy scores, “You cannot have a conflict of interest.” At the same time, Truth{set} is working closely with the data providers to score their data and to help them improve their accuracy. The goal is to create an expectation among marketers that if data is accurate, it will come with a score from Truth{set}.

“There’s a FOMO thing here — if you’re not being measured, what are you hiding?” McKinley said.

Startups – TechCrunch

The secret to trustworthy data strategy

Shortly after its use exploded in the post-office world of COVID-19, Zoom was banned by a variety of private and public actors, including SpaceX and the government of Taiwan. Critics allege its data strategy, particularly its privacy and security measures, were insufficiently robust, especially putting vulnerable populations, like children, at risk. NYC’s Department of Education, for instance, mandated teachers switch to alternative platforms like Microsoft Teams.

This isn’t a problem specific to Zoom. Other technology giants, from Alphabet, Apple to Facebook, have struggled with these strategic data issues, despite wielding armies of lawyers and data engineers, and have overcome them.

To remedy this, data leaders cannot stop at identifying how to improve their revenue-generating functions with data, what the former Chief Data Officer of AIG (one of our co-authors) calls “offensive” data strategy. Data leaders also protect, fight for, and empower their key partners, like users and employees, or promote “defensive” data strategy. Data offense and defense are core to trustworthy data-driven products.

While these data issues apply to most organizations, highly-regulated innovators in industries with large social impact (the “third wave”) must pay special attention. As Steve Case and the World Economic Forum articulate, the next phase of innovation will center on industries that merge the digital and the physical worlds, affecting the most intimate aspects of our lives. As a result, companies that balance insight and trust well, Boston Consulting group predicts, will be the new winners.

Drawing from our work across the public, corporate, and startup worlds, we identify a few “insight killers” — then identify the trustworthy alternative. While trustworthy data strategy should involve end users and other groups outside the company as discussed here, the lessons below focus on the complexities of partnering within organizations, which deserve attention in their own right.

Insight-killer #1: “Data strategy adds no value to my life.”

From the beginning of a data project, a trustworthy data leader asks, “Who are our partners and what prevents them from achieving their goals?” In other words: listen. This question can help identify the unmet needs of the 46% of surveyed technology and business teams who found their data groups have little value to offer them.

Putting this to action is the data leader of one highly-regulated AI health startup — Cognoa — who listened to tensions between its defensive and offensive data functions. Cognoa’s Chief AI Officer identified how healthcare data laws, like the Health Insurance Portability and Accountability Act, resulted in friction between his key partners: compliance officers and machine learning engineers. Compliance officers needed to protect end users’ privacy while data and machine learning engineers wanted faster access to data.

To meet these multifaceted goals, Cognoa first scoped down its solution by prioritizing its highest-risk databases. It then connected all of those databases using a single access-and-control layer.

This redesign satisfied its compliance officers because Cognoa’s engineers could then only access health data based on strict policy rules informed by healthcare data regulations. Furthermore, since these rules could be configured and transparently explained without code, it bridged communication gaps between its data and compliance roles. Its engineers were also elated because they no longer had to wait as long to receive privacy-protected copies.

Because its data leader started by listening to the struggles of its two key partners, Cognoa met both its defensive and offensive goals.

Startups – TechCrunch

[data.world in Austin Business World] A DATA DUMP DURING CRISIS

Yoga and mental health Slack channels, talks on Hindu philosophy and how to make a killer beef stroganoff. These are just some of the ways Data.world team mebers are boosting their coworkers’ morale during these tough times.

Read more here.

The post [data.world in Austin Business World] A DATA DUMP DURING CRISIS appeared first on OurCrowd.

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Work From Home Jobs – Try Data Entry

Try to network with business proprietors to build your connections. Enables you to you conduct a lot, including getting within your home and creating a good support physique. Sometimes, you just need to step from the computer.

Remember one thing, nothing works on its own, you really have to make it work. Aren’t applies to one’s home based work also. After all, how a lot know concerning your home based work? Is your customer resonant? So you need in order to out and inform that. Look at the right communication channels and work accordingly.

First thing to know is doesn’t everyone can write. Do not have to have for you to become an English professor by any means, but you should be in the position to express yourself and put your just what it paper. A whole lot of the writing assignments you will encounter for blogs, web 2 . and even reviews are written an everyday very lazy tone training must be done can make. One of the best advantages of work from home freelance writing is an individual are in whole control. You alone choose which assignments you will take allowing you the freedom to pick a topic you’re familiar via.

Not everyone has found a job that they love. Therefore if you honestly expect to keep working for your personal current employer but at home, talk to your boss to understand how to render it happen. May possibly be amazed at their willingness to aide you to.

You must have a lot of discipline as the work at home Dad. It is very easy to obtain side-tracked by all relatives chores that must be done. However the way I look on-line is, if I’ve sent my newborn baby to daycare for a couple of hours to get some work done, then exactly what I’ll achieve I won’t clean household or buy things etc., I’ll switch on my own computer and be to work.

One among the first steps that should be taken your market start-up phase of your home business is to establish a reasonable advertising price range. Generally, your home business advertising budget should be anywhere from two to seven percent of their total revenue. If you should be able it, 10 % is considered ideal.

It will most definately invite an unwanted situations and frustrations for your company. If you have never had much money before you can’t imagine what will change for that worst within money a person are only thinking to the good tasks.

[data.world in MenaFN] Data.World And John Snow Labs Partner To Make 2,200 Current, Linked, And Expert-Curated Healthcare Datasets Available To Covid-19 Researchers & Data Scientists

“David Talby, CTO of John Snow Labs, echoed the sentiment. ‘Healthcare data scientists & analysts need the right data and context to succeed, and we’re committed to clearing the way to get them there. The combination of our medical domain expertise, three levels of quality reviews, and always-current data with data.world’s discovery, community, and enrichment capabilities are a natural match to help accelerate the healthcare research community.’”

Read more here.

The post [data.world in MenaFN] Data.World And John Snow Labs Partner To Make 2,200 Current, Linked, And Expert-Curated Healthcare Datasets Available To Covid-19 Researchers & Data Scientists appeared first on OurCrowd.

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Census raises $4.3M seed to put product info in cloud data warehouses to work

Companies spend inordinate amounts of time and money building data warehouses and moving data from enterprise applications. But once they get the data in, how do they get specific information like product data back out and distribute it to business operations, who can use it to better understand customers? That’s where Census comes in. It builds a layer on top of the data warehouse that makes it easy for the data team to distribute product data it where it’s needed.

The company announced a $ 4.3 million seed today, although it closed last year while they were still building the product. That round was led by Andreessen Horowitz with help from SV Angel and a number of angel investors.

Census CEO Boris Jabes says the company was founded to solve this problem of data distribution from a cloud data warehouse. He says for starters they are concentrating on product data.

“The product is designed to sync data directly from cloud data warehouses like Snowflake, BigQuery and Redshift […] and the main reason we did that was people really needed to get access to this kind of product data and all this data that’s locked in all their systems and take advantage of it,” Jabes explained.

He says that the first step is to make the product data sitting in the data warehouse actionable for the organization. They are working with data teams at early customers to remove the complexity of getting that data out of the warehouse and putting it to work in a more automated fashion.

They do this by creating a unified schema that sits on top of the data in the warehouse and makes it easier to distribute it to the teams that need it inside the organization. It essentially acts as a middleware layer on top of the warehouse that you can take advantage of without having to write code to decide where data might be most useful.

David Ulevitch, who led the investment at a16z says that removing this manual part of the process is highly valuable. “For years, organizations have had to do the frustrating task of manually syncing data between dozens of apps. This friction is especially painful now that data has become critical to every team in a business, from product to sales. Census sets a new standard for how product-led SaaS companies can operationalize data,” he said in a statement.

Jabes understands these are difficult times for every business, and especially an early stage startup, but he says they are focusing on an aspect of the business that potential customers need.

“We’ve seen companies actually spending time trying to tackle some of these data problems […] so I’m still optimistic,” he says.

Startups – TechCrunch

Toro snags $4M seed investment to monitor data quality

Toro’s founders started at Uber helping monitor the data quality in the company’s vast data catalogs, and they wanted to put that experience to work for a more general audience. Today, the company announced a $ 4 million seed round.

The round was co-led by Costanoa Ventures and Point72 Ventures with help from a number of individual investors.

Company co-founder and CEO Kyle Kirwin says the startup wanted to bring the kind of automated monitoring we have in applications performance monitoring products to data. Instead of getting an alert when the application is performing poorly, you would get an alert that there is an issue with the data.

“We’re building a monitoring platform that helps data teams find problems in their data content before that gets into dashboards and machine learning models and other places where problems in the data could cause a lot of damage,” Kirwin told TechCrunch.

When it comes to data, there are specific kinds of issues a product like Toro would be looking at. It might be a figure that falls outside of a specific dollar range that could be indicative of fraud, or it could be simply a mistake in how the data was labeled that is different from previous ways that could break a model.

The founders learned the lessons they use to build Toro while working on the data team at Uber. They had helped build tools there to find these kinds of problems, but in a way that was highly specific to Uber. When they started Toro, they needed to build a more general purpose tool.

The product works by understanding what it’s looking at in terms of data, and what the normal thresholds are for a particular type of data. Anything that falls outside of the threshold for a particular data point would trigger an alert, and the data team would need to go to work to fix the problem.

Casey Aylward, vice president at Costanoa Ventures likes the pedigree of this team and the problem it’s trying to solve. “Despite its importance, data quality has remained a challenge for many enterprise companies,” he said in a statement. He added, “[The co-founders] deep experience building several of Uber’s internal data tools makes them uniquely qualified to build the best solution.”

The company has been at this for just over a year and have been keeping it lean with 4 employees including the two co-founders, but they do have plans to add a couple of data scientists in the coming year as they continue to build out the product.

Startups – TechCrunch

Indonesian startup Delman raises $1.6 million to help companies clean up data

Delman, a Jakarta-based data management startup, has raised $ 1.6 million in seed funding. The round was led by Intudo Ventures, with participation from Prasetia Dwidharma Ventures and Qlue Performa Indonesia, and will be used to establish a research and development center and hire software engineers and data scientists.

Delman was founded in 2018 by chief executive officer Surya Halim, chief product officer Raymond Christopher and chief technology officer Theo Budiyanto, who were classmates at the University of California, Berkeley. After graduation, they worked at tech companies in Silicon Valley, including Google and Splunk, before deciding to focus on the Indonesian market.

Originally launched as an end-to-end big data analytics provider, Delman shifted its focus to data preparation and management after talking to clients in Indonesia, said Halim. Many companies said they had budgeted for expensive data analytics solution, but then realized their data was not ready for analysis because it was spread across multiple formats. Delman’s mission is to make it easier for data engineers and scientists to do their jobs by cleaning up and preparing data.

Halim says many large companies in Indonesia typically spend up to $ 200,000 to clean and warehouse data, but Delman gives them a more cost-efficient and faster alternative.

“We have the capability to do analytics and data visualization for clients, but there are so many established companies that already do that, which is why we shifted our business model to something more niche and needed,” said Halim. “It also enables us to open our door to partner with everyone doing data analytics services.”

While newer companies and startups have cleaner datasets, Halim said many older Indonesian companies, especially ones with branches in multiple cities, often have large amounts of data spread across pen-and-paper ledgers, Excel spreadsheets and other software. The data may also have code, keywords and typos that need to be corrected.

“It’s easier for a new company, because everything is already standardized,” Halim said, “But if a company that was established in the 1970s wants to unify previous generations of data to integrate it into their system and keep notes on what customer behavior is like in order to compete with up-and-coming companies, then they need to have a data-driven policy.”

Delman is industry-agnostic and its clients range from large corporations and consulting firms to government agencies. Its customers have included PWC and Qlue. Halim said that the startup plans to expand into other Southeast Asian markets and expects that as COVID-19 changes the way people work, companies will want to invest more heavily in their IT infrastructure and make their databases easier to access outside of a central location.

In a press statement, Intudo Ventures founding partner Eddy Chan said, “By combining a highly localized approach with global technical expertise, Delman is providing Indonesian businesses with Indonesian-developed big data solutions, ultimately leading to better outcomes for end-users. Since meeting the Delman founding team in Silicon Valley in 2017, we have witnessed their growth as a management team, and are excited to continue to support them in their entrepreneurial journey ahead.”

Startups – TechCrunch

Data Entry And Internet Marketing

Does your program genuinely care for consumers and promoters exact same. If you have any hint that organization deliberately doesn’t put care into their promoters or consumers, jump ship!

When you’re employed outside within the home, you’ll get observe your kids much. A great deal more work for the comfort of one’s own home, you will be there whenever your kids need you. Just also save you money on having to cover for a babysitter.

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Going online to do freelance job is definitely one of the best stay within the jobs regardless how far along you are. Depending on this skills, hobbies and interests, there are very many options even when ever you work at home with a new baby. Writing articles, data entry, medical transcription and virtual assistantship are simply some with the choices for ladies who work at home.

Either really can start quite business from scratch, meaning you guide you with organization plan and execute each and every aspect of it yourself anyone find an existing company to partner that includes. A franchise is one of them of a home business product. An internet based clients are another representation.

Hosting Company. You need to host function with an efficient hosting carrier. Hosting charges depend basically of the hosting period and plus you pick and choose. I recommend hosting your website over an extended period your time and energy preferably a couple of years to you are able to. It’s not advisable using FREE Web hosts.

Second thing to know is to commit to writing. Make money online freelance writing can be very lucrative and praising. Like anything else, money will not fall personal lap even though this may be the internet. The truth is that you have a lot of competition e-commerce. What will make you better than individuals is your commitment and hard work. With that said however, you will be able condition expertise goodbye for that daily commute and function in your pajamas from your lounge chair.

If you are traveling away for business, you can deduct these costs against your duty. But you cannot you actually are traveling purely for pleasure. Can be smart, as travel expenses are completely deductible and half of your meals are as well.

Irony alert! Data protection agency complains it can’t get access to private Whois data

 DomainIncite.com: A European data protection authority has complained to ICANN after a registrar refused to hand over one of its customers’ private Whois records, citing the GDPR data protection regulation, according to ICANN. Compounding the irony, the DPA wanted the data as part of its probe into an alleged GDPR violation at the domain in ques…
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