Datafold is solving the chaos of data engineering

It seemed so simple. A small schema issue in a database was wrecking a feature in the app, increasing latency and degrading the user experience. The resident data engineer pops in a fix to amend the schema, and everything seems fine — for now. Unbeknownst to them, that small fix completely clobbered all the dashboards used by the company’s leadership. Finance is down, ops is pissed, and the CEO — well, they don’t even know whether the company is online.

For data engineers, it’s not just a recurring nightmare — it’s a day-to-day reality. A decade plus into that whole “data is the new oil” claptrap, and we’re still managing data piecemeal and without proper systems and controls. Data lakes have become data oceans and data warehouses have become … well, whatever the massive version of a warehouse is called (a waremansion I guess). Data engineers bridge the gap between the messy world of real life and the precise nature of code, and they need much better tools to do their jobs.

As TechCrunch’s unofficial data engineer, I’ve personally struggled with many of these same problems. And so that’s what drew me into Datafold.

Datafold is a brand-new platform for managing the quality assurance of data. Much in the way that a software platform has QA and continuous integration tools to ensure that code functions as expected, Datafold integrates across data sources to ensure that changes in the schema of one table doesn’t knock out functionality somewhere else.

Founder Gleb Mezhanskiy knows these problems firsthand. He’s informed from his time at Lyft, where he was a data scientist and data engineer, and later transformed into a product manager “focused on the productivity of data professionals.” The idea was that as Lyft expanded, it needed much better pipelines and tooling around its data to remain competitive with Uber and others in its space.

His lessons from Lyft inform Datafold’s current focus. Mezhanskiy explained that the platform sits in the connections between all data sources and their outlets. There are two challenges to solve here. First, “data is changing, every day you get new data, and the shape of it can be very different either for business reasons or because your data sources can be broken.” And second, “the old code that is used by companies to transform this data is also changing very rapidly because companies are building new products, they are refactoring their features … a lot of errors can happen.”

In equation form: messy reality + chaos in data engineering = unhappy data end users.

With Datafold, changes made by data engineers in their extractions and transformations can be compared for unintentional changes. For instance, maybe a function that formerly returned an integer now returns a text string, an accidental mistake introduced by the engineer. Rather than wait until BI tools flop and a bunch of alerts come in from managers, Datafold will indicate that there is likely some sort of problem, and identify what happened.

The key efficiency here is that Datafold aggregates changes in datasets — even datasets with billions of entries — into summaries so that data engineers can understand even subtle flaws. The goal is that even if an error transpires in 0.1% of cases, Datafold will be able to identify that issue and also bring a summary of it to the data engineer for response.

Datafold is entering a market that is, quite frankly, as chaotic as the data being processed. It sits in the key middle layer of the data stack — it’s not the data lake or data warehouse for storing data, and it isn’t the end user BI tools like a Looker, Tableau or many others. Instead, it’s part of a number of tools available for data engineers to manage and monitor their data flows to ensure consistency and quality.

The startup is targeting companies with at least 20 people on their data team — that’s the sweet spot where a data team has enough scale and resources that they are going to be concerned with data quality.

Today Datafold is three people, and will be debuting officially at YC’s Demo Day later this month. Its ultimate dream is a world where data engineers never again have to get an overnight page to fix a data quality issue. If you’ve been there, you know precisely why such a product is valuable.

Startups – TechCrunch

Rippling nabs $145M at a $1.35B valuation to build out its all-in-one platform for employee data

Big news today the world of IT startups targeting businesses. Rippling, the startup founded by Parker Conrad to take on the ambitious challenge of building a platform to manage all aspects of employee data, from payroll and benefits through to device management, has closed $ 145 million in funding — a monster Series B that catapults the company to a valuation of $ 1.35 billion.

Parker Conrad, the CEO who co-founded the company with Prasanna Sankar (the CTO), said in an interview that the plan will be to use the money to continue its own in-house product development (that is, bringing more tools into the Rippling mix organically, not by way of acquisition) but also to have it just in case, given everything else going on at the moment.

“We will double down on R&D but to be honest we’re trying not to change the formula too much,” Conrad said. “We want to have that discipline. This fundraising was opportunistic amid the larger macroeconomic risk at the moment. I was working at startups in 2008-2009 and the funding markets are strong right now, all things considered, and so we wanted to make sure we had the stockpile we needed in case things went bad.”

This latest round included Greenoaks Capital, Coatue Management and Bedrock Capital, as well as existing investors including Kleiner Perkins, Initialized Capital and Y Combinator. Founders Fund partner Napoleon Ta will join Rippling’s board of directors. Founders Fund had also backed Zenefits when Parker was at the helm, and from what we understand, this round was oversubscribed — also a big feat in the current market, working against a lot of factors, including a wobbling economy.

It is a big leap for the company: it was just a little over a year ago that it raised a Series A of $ 45 million at a valuation of $ 270 million.

This latest round is notable for a few reasons.

First is the business itself. HR and employee management software are two major areas of IT that have faced a lot of fragmentation over the years, with many businesses opting for a cocktail of services covering disparate areas like employee onboarding, payroll, benefits, device management, app provisioning and permissions and more. That’s been even more the case among smaller organizations in the 2-1,000 employee range that Rippling targets.

Rippling is approaching that bigger challenge as one that can be tackled by a single platform — the theory being that managing HR employee data is essentially part and parcel of good management of IT data permissions and device provision. This funding is a signal of how both investors and customers are buying into Rippling and its approach, even if right now the majority of customers don’t onboard with the full suite of services. (Some 75% are usually signing up with HR products, Conrad noted.)

“We like to think of ourselves as a Salesforce for employee data,” Conrad said, “and by that, we think that employee data is more than just HR. We want to manage access to all of your third-party business apps, your computer and other devices. It’s when you combine all that that you can manage employees well.”

The company is gradually adding more tools. Most recently, it’s been launching new tools to help with job costing, helping companies track where employees are spending time when working on different projects, a tool critical for IT, accounting and other companies where employees work across a number of clients. Other new tools include SMS communications for “desk-less” workers and more accounting integrations.

Second is the founder. You might recall that Conrad was ousted from his previous company, Zenefits (taking on a related, but smaller, challenge in payroll and benefits), over a controversy linked to compliance issues and also misleading investors. But if Zenefits was finished with Conrad, Conrad was not finished with Zenefits — or at least the problem it was tackling. This funding is a testament to how investors are putting a big bet on Conrad himself, who says that a lot of what he has been building at Rippling was what he would have done at Zenefits if he’d stayed there.

“Once you’re lucky, twice you’re good,” said Mamoon Hamid, a partner at Kleiner Perkins, in a separate statement. “Parker is a true product visionary, and he and his team are solving an enormous pain point for businesses everywhere. We’re thrilled to continue partnering with Rippling as demand for their platform dramatically increases in this era of remote work.”

“Rippling is not just a superior payroll company, but something much broader: they’ve built the system of record for all employee data, creating an entirely new software category. Rippling’s massive market opportunity is to streamline the employee life cycle, from software to payroll to benefits, and fundamentally improve the way businesses hire and manage their employees,” said Ta in a statement.

Third is the context in which this round is coming. We’re in the midst of an economic downturn caused in part by a global health pandemic, and that’s leading to a lot of companies curtailing budgets, reducing headcount and potentially shutting down altogether. Ironically, that force is also propelling companies like Rippling full steam ahead.

Its SaaS model — priced at a flat $ 8 per person per month — not only fits with how many businesses are being run at the moment (primarily remotely), but Rippling’s purpose is specifically geared to helping businesses both onboard and offboard employees more efficiently, the kind of software that companies need to have in place to fit how they are working right now.

Updated with commentary from an interview with Conrad.

Startups – TechCrunch

Part 2/6 of the 60 Minute Presentation for a Head of Growth Role at a Startup: Data Friendliness and Follow Every Penny.

Marketers and sales people can get a reputation for speaking in esoteric jargon, especially when interviewing. So I led with the fact I'm good with numbers knowledge and to show I'd always use data to inform decisions and be incredibly cost efficient. First post in series – here

Get friendly with data and money

  1. 'We are' not 'We should' – preface.

Time is fleeting in a startup. What you need from a growth lead is the answer backed by data, not a frivolous omnidirectional debate. I have my North Star Metric, that's my goal.

When I come to you with a direction, my phrasing will always be 'we're going to' or 'we've started to'.

This is because the data has been exported, analysed, documented and already consumed to inform my decision. By the time my proposal is shown, it will be inscrutable and proven with the research I undertook to reach the decision, I'm simply letting you know that the work has been done and this is the best step to take. My workings will always be written in a workable doc with precise links to the reporting I have extracted the data from.

  1. 'Thou shalt attribute.'

I cannot stand grey areas in marketing, there are no excuses. Not having attribution partners in place or an absolute key understanding of your purchase pathways is wastage. If my budget is $ 10 or $ 10m, understanding exactly where that money went and what the ROI was will be incredibly significant.

Example Retained agencies.

Agencies will be held accountable to report on all hours of the work they undertook for the company, they will report on ROAS and specific time taken on projects.

Be pedantic, or bring the skills in house.

A good rule of thumb is that 1 hour of work needs 30 seconds explaining; if it requires less, it is perhaps not an hour's work. Push for details.

Example Paid Social

I am an expert at reading whether an ad is good or not with the data, I guarantee my ads will deliver. The learnings and data were there to be read and understood and learnt from, so I did.

Unnecessary charges based on having poor or no attribution partners whose entire reason for existing is to make sure you're not overpaying and to source the purchase is ridiculous.

Unnecessary charges based on poor construction of your campaigns and then overpaying need never happen.

One look will tell you Snapchat's UI could be operated by toddlers, all it requires is learning the format of successful ad building based on the readily available data.

Plug into the right places, pay for the right conversions, and understand the terminology exceptionally and monitor intimately.

  1. 'High standards encourage excellent standards of practice'

Knowing where you're starting from with the specific data you can acquire, down to the minutia, will absolutely help you grow healthier and better.

Every step you take that leads to a measurable improvement in growth, IS growth.

When it comes to managing a team, being able to prove improvements or detriments makes for an easy performance review. Not just for your employee, but for yourself.

Though very black and white as a review process, it is always your responsibility to create an environment that encourages learning and growth, if your team member is not improving, it is your responsibility to better this environment and get them on the path.

An upwards curve following a performance review represents your learning, their learning and better results.

  1. 'Plot and predict'

The best heads of growth work closely with the money. This is logical when you consider that they're in control of a huge portion of the marketing spend.

A successful growth expert will be able to monitor budgets based on previous campaigns and predict the likelihood of having more or less money to spend the next month, they're in a luxurious position of being able to control growth if they're seeing success.

A growth expert can plot the course of growth in line with the company's motives.

The company may look to raise, the company might be on the sliding path to be erased; it is the growth lead's job to remain at the forefront to plot out projections and predict the good and the bad.

This means answering questions; 'How many conversions can we get for X?' 'Can we carry on growing if we spend X per conversion?' 'How much revenue can we generate with X on growth?' 'What's our runway if we cut all growth?'

They are the very much the engineer of the marketing team.


This is the end of slide one – next slide is manufacturing creativity; coming tomorrow.

Let me know if you have any q's or comments 🙂

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Startups – Rapid Growth and Innovation is in Our Very Nature!

Skills To Do Data Entry Do At Home

Now that most of us have explored the benefits, it one more important in order to at the drawbacks. Obviously working from isn’t for you to be perfect either. These are six disadvantages of working online.

Hence, 90% of the population in this world needs start off your own business, your own home based business. In this article, we become looking at the top excellent why people need to work from home and generate residual income that will feed and also your your family for their lives.

Take business travel if you must. You cannot do several home: you’ve got to go along with clients or investors. Must how much you spend while on a business path. You will be able to deduct these expenses from your taxes. Even though you simply drive back and forth inside same day, you might still deduct what gas take you.

One for the first steps that end up being taken in start-up phase of your home business end up being establish an affordable advertising cost range. Generally, your home business advertising budget should be anywhere from two to seven percent of their total gross sales. If you are able it, 10 percent is considered ideal.

Take breaks. Breaks aren’t just ways to leave work; may well essential for time management, especially with computer jobs or writing jobs. Since you naturally blink less when staring at computer screens, your eyes become irritated faster. Your posture, hands and arms also have problems with continuous hunching and keyboard skills. Over time, your quality do the job degrades from physical borders. Try stretching or getting clean air at least 10 minutes for every hour you type.

Some people also have luck with work at home job paid membership sites such as Home Job Stop. You aren’t paying for job there, you’re having to pay for listings may well help you to identify an occupational.

One the simplest way to work part time from residence is what as known as affiliate marketing. First of all, affiliate marketing is when you choose a product to promote, and this company pays you with a commission.

The Growing Importance Of Data Privacy & Its Value To Businesses

Data privacy is a bigger issue now than ever before for both companies and consumers, as a hacker attack occurs once every 39 seconds. A lot of private information is stored online and in the company’s databases, so a data breach can lead to serious issues for consumers and businesses alike.

Data is a vital asset for any business, so the privacy of data needs to be taken seriously. If you want to learn about it in a broader sense, Prolifics explains it in great detail.

But for now, let’s focus on the value and the growing importance that data has for your business.

Why Is Data Privacy So Important For Your Business?

Without proper protocols in place, your business probably wouldn’t be able to survive for long. There are many reasons why data privacy should be a concern for all businesses and why its importance is so great. However, the four reasons listed below stand above the rest.

1. Preventing Data Breaches

With the threat of data breaches rising every day, organizations need to have strong security safeguards in place. The main goal is to protect customers’ personal data. As soon as you have those safeguards, the chances of security incidents that lead to data breaches will decrease significantly.

2. Complying With Regulations

Organizations that don’t have a way to ensure privacy protections aren’t just irresponsible, they also break the law. There are requirements that state organizations that fail to comply with laws and regulations regarding data privacy may face monetary fines as high as tens of millions of dollars. Furthermore, non-compliance with these laws can result in up to 20-year penalties.

3. Supporting Ethics

Most organizations follow an established code of ethics, and even if they don’t, they have to follow certain ethical practices if they want their business to succeed. One of these ethical policies usually states that all confidential information a customer has shared with the company needs to be handled responsibly. This means that this information can only be used for business purposes and must never be used in a way that might harm the customer.

4. Maintaining Customer Loyalty

Customers want to know their personal information is safe and that companies do everything to keep their data private. A large number of customers will stop doing business with a company in the case of a significant personal data leak and they will simply switch to a competitor.

How To Solve Challenges Created By Data Privacy Regulations

Data privacy regulations come with some challenges. While they can sometimes be hard to deal with, all you need to do is learn how to approach this issue.

Implementing Data Privacy

Data privacy touches on multiple parts of every business. Unfortunately, most companies tack data privacy to their IT security plan and think that’s enough, but it certainly isn’t. This shows that you only see data privacy as an afterthought and don’t take it seriously enough.

To implement data privacy the right way, it needs to be at the center of your data strategy and all staff members need to be trained in it.

Find A Way To Manage Access Control

A large number of data privacy breaches are caused by access control that wasn’t properly managed within a company. Keep in mind that technology isn’t the only thing you need to worry about, people and processes also matter.

Unfortunately, human employees can pose a threat to data privacy, especially within an organization that has a lot of employees, as this makes it harder to manage user access. To solve this issue, you need to have strong data governance processes as well as good data architecture.

Don’t Store More Data Than Necessary

When big data first appeared, there was a lot of hype surrounding it and many organizations believed that because they can store a lot of data, they should collect as much data as possible. However, when you think about the implications this could have, you’ll realize why this is a bad idea.

Don’t keep data just for the sake of keeping it because this broadens the surfaces hackers can target and steal data from. Instead, make a good balance between the value of collecting and storing large quantities of data on one hand and meeting compliance and security regulations on the other.

Learn To Differentiate Between Types Of Data

Not all data is created equal and some types of it need to have better security than others. You need to discover and classify all data so you can be sure where it’s located and how sensitive it is. This will allow you to treat all data uniquely.

Manage Data On All Devices

There are a lot of factors you need to consider that can make data privacy harder to control. One of those things is multiple types of devices, especially in organizations where employees are allowed to bring their own devices to work.

If you have this kind of policy, either re-think it or make sure that all devices employees use comply with data privacy regulations.


Data privacy has been an ongoing issue for years, and it will continue to cause problems for organizations that don’t take it seriously enough. However, if you carefully consider everything you just read, you can ensure that your organization is safe, trustworthy, and follows all regulations.




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StartUs Magazine

Madrid-based GeoDB smashes Seedrs campaign by 150% with €1.6 million, aiming to reward users for their big data

Spanish startup GeoDB has announced achieving a 150% overfunding of its recent Seedrs equity crowdfunding campaign, landing around €1.6 million. Founded in 2018, GeoDB aims to revolutionise the way big data is commercialized, making the system fairer for both users and buyers. 

GeoDB is effectively taking on the big data industry as a whole, heading first with a platform that is going to change the way people consume, share and access big data. The team plans to change the rules for both sides with its new blockchain-based data-sharing model. Users consent to share their data anonymously and automatically, making it accessible to buyers who can consume this data together with analytical tools available on the platform. This will make it possible for ordinary users to be compensated for their data generation, in a unique way.

The company is set to return value to its users for sharing data, which will be done via their tokenized platform and to allow data buyers to access trusted, quality and accurate data. The rewards are compensated with tokens that can be converted to crypto, fiat, or on-platform discounts and perks. The team aims to close the gap between data generators and data buyers, therefore solving huge inefficiencies in the industry, eliminating intermediation and allowing faster and frictionless transactions. GeoDB has already attracted an active user base of over 12 million users from 150 countries and established a number of strategic partnerships with the leading industry representatives, such as Grupo Next, Wola and others.

To maximize value and user rewards, GeoDB has deployed targeted apps to collect user data. One example is GeoCash, which captures location data and information about the user’s mobile device, such as the screen size and operating system, without violating privacy. As reported by the GeoDB team, GeoCash is showing an impressive growth potential generating over 100k active users in more than 50 countries worldwide.

The crowdfunding campaign launched at the beginning of March 2020 has once again proved the effectiveness and the growing demand for their solutions. More than 650 investors have joined the campaign and the results turned out to be outstanding. 

The company is now heading to an active business development phase to continue onboarding new strategic partners and building a global presence of GeoDB. The GEO token, which is a representation of data’s value in the form of a tradable virtual asset, is already listed on several crypto exchanges and the team is also focused on constantly negotiating with more leading exchanges to provide enough liquidity for the ecosystem’s participants. 

Considering the fact that only 5-10% of the data is being exploited today, GeoDB is taking a step towards a 100% data usage, whereby all the parties within the ecosystem are encouraged by transparency and data efficiency.


Work The Data Entry And You

It’s pretty common for people who internet marketing to understand they upwards with more distractions than they’d the desired. Do you have pets that need attending? Even though they spent the day by themselves when you had been working, you might surprised discover how more and more attention appear to think that they need just because you’re to your house.

Have a budget – Will be possible to limit the amount you want to invest, but you will need some money. Plus, as the ease in starts making money, you require to reinvest in your business. So, you will both need money to reside on a few money to start your work from home business.

Take breaks or cracks. Breaks aren’t just ways to emerge from work; however essential for time management, especially with computer jobs or writing jobs. Because you naturally blink less when staring at computer screens, your eyes become irritated faster. Your posture, hands and arms also are afflicted with continuous hunching and entering. Over time, your quality do the job degrades from physical borders. Try stretching or getting outside air at least 10 minutes for every hour you type.

I’ve said it before and I’ll say it again: the associated with work you may do out of your home depends on ones skills and interests. Actually be broader than you think, specifically you don’t feel although you receive the skills for that work at home jobs you’ve involving so quite a bit.

You in order to be keep it clean and treat it like the vessel to every one of your achieving your goal. It actually takes your biggest of your old normal work car because without it you can’t get to work.

Yes, pregnancy poses some challenges and limitations having said that clearly has no effect on your ability to think or speak. Do skilled at a foreign dialect? Do you have excellent communication skills? Concerning sales and marketing capability?

When you discover which business fits vehicle better than any other business, you have to have the personal strength and commitment to target only on that organization. Stop trying out something else every week that sounds good. Information that you understand the R.E.R.F.E.C.T. home business you discovered in step one and work at it if you do not make it a glory. Yes, it will take some labor. Expect it. And it will quite likely take more than you sense. So what? Wouldn’t it be this to finally make your home business dream possible?

They do buy from you, or they tend to work with you in a questionable income scheme relationship. Usually this is they they are way too timid or not assertive enough to say no. So they agree avoid a confrontation. Certainly they don’t get satisfaction of this product or service and/or they never do will be necessary greatest and fullest in the business. You’ve wasted your time with somebody who wasn’t serious and a different inividual feels like they got burned. Everybody loses.

Taiwan-based TNL Media Group raises $8 million to build its publishing and data analytics businesses

Since launching in 2013, Taipei-based TNL Media Group has grown from an independent news site to a media company with several online publishing verticals and a data analytics business. The company, formerly known as The News Lens, announced today that it has raised $ 8 million from New York-based investment firm Palm Drive Capital, as part of its Series D round.

TNL Media Group’s last funding announcement was a Series C round announced two years ago. Co-founder and chief executive officer Joey Chung told TechCrunch that its latest infusion of funding will be used to add more media verticals, continue TNL Media Group’s international expansion and finish its current pipeline of data analytics and tech service products.

TNL Media Group’s previous investors include North Base Media, the firm co-founded by Washington Post and Wall Street Journal veteran Marcus Brauchli (who is also a member of the startup’s board). The News Lens launched seven years ago as a bilingual site to give millennial readers an alternative to traditional media outlets in Taiwan, where coverage is often sharply divided along political lines and traffic is driven by celebrity gossip and other tabloid fodder.

Since then, it has grown through a series of launches and acquisitions. In addition to its main news site, it also operates separate sites for tech, sports, lifestyle, gadgets and entertainment content. Earlier this year, TNL Media Group acquired Taiwanese mobile ad technology startup Ad2iction, a cloud-based platform for brands to manage and create digital ads.

Because TNL Media Group already has offices in Taiwan and Hong Kong, and also has a media vertical dedicated to covering Southeast Asia, Chung said the company is now looking for opportunities to expand there. At the same time, he added that TNL Media Group has “had numerous very late-stage conversations” about partnerships to launch in Japan.

The company’s media verticals complement its data analytics business because it is able to draw on TNL Media Group’s user base for data, which Chung said is “one of the largest readership pools for digital audiences in the greater China market.”

On average, TNL Media Group’s sites have around 14 million monthly unique users. Its data analytics business, which launched within the past year, currently has about three to five clients per month. “But of course, we are planning for that to be ramped up substantially in the coming months and years, and that will gradually grow to become a very important part of our entire business portfolio,” Chung said.

TNL Media Group’s other products include mobile ad tech, digital ticketing services, online events and online classes, and a content management system (CMS) it will start licensing to other companies.

Chung said that by the end of this year, many of these products will be integrated with its readership and data to develop a demand-side platform (DSP, a tool that connects ad buyers with publishers) and a data management platform that are already in production.

In a press statement about its investment in TNL Media Group, Palm Drive Capital managing partner Nick Hsu said, “Palm Drive Capital focuses on investing in global technology startups using software to transform traditional industries. This is evident in the media industry, particularly as Taiwan’s online ad expenditure has already reached over one billion U.S. dollars and is estimated to grow to 1.65 billion U.S. dollars by 2021. Having known the TNL Media Group team for years, we see massive potential to leverage data to drive growth, consolidation, and international expansion in the media industry.”

Startups – TechCrunch

Hevo draws in $8 million Series A for its no-code data pipeline service

Hevo founders Manish Jethani and Sourabh Agarwal

According to data pipeline startup Hevo, many small- to medium-sized companies juggle more than 40 different applications to manage sales, marketing, finance, customer support and other operations. All of these applications are important sources of data that can be analyzed to improve a company’s performance. That data often remains separate, however, making it difficult for different teams to collaborate.

Hevo enables its clients’ employees to integrate data from more than 150 different sources, including enterprise software from Salesforce and Oracle, even if they don’t have any technical experience. The company announced today that it has raised an $ 8 million Series A round led by Singapore-based venture capital firm Qualgro and Lachy Groom, a former executive at payments company Stripe.

The round, which brings Hevo’s total raised so far to $ 12 million, also included participation from returning investors Chiratae Ventures and Sequoia Capital India’s early-stage startup program Surge. The company was first covered by TechCrunch when it raised seed funding in 2017.

Hevo’s Series A will be used to increase the number of integrations available on its platform, and hire sales and marketing teams in more countries, including the United States and Singapore. The company currently has clients in 16 markets, including the U.S., India, France, Australia and Hong Kong, and counts payments company Marqeta among its customers.

In a statement, Puneet Bysani, tech lead manager at Marqeta, said, “Hevo saved us many engineering hours, and our data teams could focus on creating meaningful KPIs that add value to Marqeta’s business. With Hevo’s pre-built connectors, we were able to get data from many sources into Redshift and Snowflake very quickly.”

Based in Bangalore and San Francisco, Hevo was founded in 2017 by chief executive officer Manish Jethani and chief technology officer Sourabh Agarwal. The two previously launched SpoonJoy, a food delivery startup that was acquired by Grofers, one of India’s largest online grocery delivery services, in 2015. Jethani and Agarwal spent a year working at Grofers before leaving to start Hevo.

Hevo originated in the challenges Jethani and Agarwal faced while developing tech for SpoonJoy’s order and delivery system.

“All of our team members would come to us and say, ‘hey, we want to look at these metrics,’ or we would ask our teams questions if something wasn’t working. Oftentimes, they would not have the data available to answer those questions,” Jethani told TechCrunch.

Then at Grofers, Jethani and Agarwal realized that even large companies face the same challenges. They decided to work on a solution to allow companies to quickly integrate data sources.

For example, a marketing team at a e-commerce company might have data about its advertising on social media platforms, and how much traffic campaigns bring to their website or app. But they might not have access to data about how many of those visitors actually make purchases, or if they become repeat customers. By building a data pipeline with Hevo, they can bring all that information together.

Hevo is designed to serve all sectors, including e-commerce, healthcare and finance. In order to use it, companies sign up for Hevo’s services on its website and employees enter their credentials for software supported by the platform. Then Hevo automatically extracts and organizes the data from those sources and prepares it for cloud-based data warehouses, such as Amazon Redshift and Snowflake. A user dashboard allows companies to customize integrations or hide sensitive data.

Hevo is among a roster of “no code, low code” startups that have recently raised venture capital funding for building tools that enable non-developers to add features to their existing software. The founders say its most direct competitor is Fivetran, an Oakland, California-based company that also builds pipelines to move data to warehouses and prepare it for analysis.

Jethani said Hevo differentiates by “optimizing our product for non-technical users.”

“The number of companies who need to use data is very high and there is not enough talent available in the market. Even if it is available, it is very competitive and expensive to hire that engineering talent because big companies like Google and Amazon are also competing for the same talent,” he added. “So we felt that there has to be some democratization of who can use this technology.”

Hevo also focuses on integrating data in real-time, which is especially important for companies that provide on-demand deliveries or services. During the COVID-19 pandemic, Jethani says e-commerce clients have used Hevo to manage an influx in orders as people under stay-at-home orders purchase more items online. Companies are also relying on Hevo to help organize and manage data as their employees continue to work remotely.

In a statement about the funding, Qualgro managing partner Heang Chhor said, “Hevo provides a truly innovative solution for extracting and transforming data across multiple data sources–in real time with full automation. This helps enterprises to fully capture the benefit of data flowing though the many databases and software they currently use. Hevo’s founders are the type of globally-minded entrepreneurs that we like to support.”

Startups – TechCrunch

Explorium reels in $31M Series B as data discovery platform grows

In a world with growing amounts of data, finding the right set for a particular machine learning model can be a challenge. Explorium has created a platform to make that an easier task, and today the startup announced a $ 31 million Series B.

The round was led by Zeev Venture with help from Dynamic Loop, Emerge, 01 Advisors and F2 Capital. Today’s investment brings the total raised to $ 50 million, according to the company.

CEO and co-founder, Maor Shlomo says the company’s platform is designed to help people find the right data for their model. “The next frontier in analytics will not be about how you fine tune or improve a certain algorithm, it will be how do you find the right data to fit into those algorithms to make them as useful and impactful as possible,” he said.

He says that companies need this more than ever during the pandemic because this can help customers find more relevant data at a time when their historical data might not be useful to help build predictive models. For instance, if you’re a retailer, your historical shopping data won’t be relevant if you are in an area where you can no longer open your store, he says.

“There are so many environmental factors that are now influencing every business problem that organizations are trying to solve that Explorium is becoming this […] layer where you search for data to solve your business problems to fuel your predictive models,” he said.

When the pandemic hit in March, he worried about how it would affect his company, and he put a hold on hiring, but as he saw business increasing in April and May, he decided to accelerate again. The company currently has 87 employees between offices in Israel and the United States and he plans to be at 100 in the next couple of months.

When it comes to hiring, he says he doesn’t try to have hard and fast hiring rules like you have a certain degree or have gone to a certain school. “The only thing that’s important is getting good people hungry to succeed. The more diverse the culture is, the more diverse the group is, we find the more fun it is for people to discover each other and to discover different cultures,” Shlomo explained.

In terms of fundraising, the while the company needs money to fuel its growth, at the same time it still had plenty of money in the bank from last year’s round. “We got into the pandemic and we didn’t know how long it’s going to last, and [early on] we didn’t yet know how it would impact the business. Existing investors were always bullish about the company. We decided to just go with that,” he said.

The company was founded in 2017 and previously raised a $ 19.1 million Series A round last year.

Startups – TechCrunch