Nov
19
2020
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Amazon S3 Storage Lens gives IT visibility into complex S3 usage

As your S3 storage requirements grow, it gets harder to understand exactly what you have, and this especially true when it crosses multiple regions. This could have broad implications for administrators, who are forced to build their own solutions to get that missing visibility. AWS changed that this week when it announced a new product called Amazon S3 Storage Lens, a way to understand highly complex S3 storage environments.

The tool provides analytics that help you understand what’s happening across your S3 object storage installations, and to take action when needed. As the company describes the new service in a blog post, “This is the first cloud storage analytics solution to give you organization-wide visibility into object storage, with point-in-time metrics and trend lines as well as actionable recommendations,” the company wrote in the post.

Amazon S3 Storage Lens Console

Image Credits: Amazon

The idea is to present a set of 29 metrics in a dashboard that help you “discover anomalies, identify cost efficiencies and apply data protection best practices,” according to the company. IT administrators can get a view of their storage landscape and can drill down into specific instances when necessary, such as if there is a problem that requires attention. The product comes out of the box with a default dashboard, but admins can also create their own customized dashboards, and even export S3 Lens data to other Amazon tools.

For companies with complex storage requirements, as in thousands or even tens of thousands of S3 storage instances, who have had to kludge together ways to understand what’s happening across the systems, this gives them a single view across it all.

S3 Storage Lens is now available in all AWS regions, according to the company.

Oct
27
2020
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Rockset announces $40M Series B as data analytics solution gains momentum

Rockset, a cloud-native analytics company, announced a $40 million Series B investment today led by Sequoia with help from Greylock, the same two firms that financed its Series A. The startup has now raised a total of $61.5 million, according to the company.

As co-founder and CEO Venkat Venkataramani told me at the time of the Series A in 2018, there is a lot of manual work involved in getting data ready to use and it acts as a roadblock to getting to real insight. He hoped to change that with Rockset.

“We’re building out our service with innovative architecture and unique capabilities that allows full-featured fast SQL directly on raw data. And we’re offering this as a service. So developers and data scientists can go from useful data in any shape, any form to useful applications in a matter of minutes. And it would take months today,” he told me in 2018.

In fact, “Rockset automatically builds a converged index on any data — including structured, semi-structured, geographical and time series data — for high-performance search and analytics at scale,” the company explained.

It seems to be resonating with investors and customers alike as the company raised a healthy B round and business is booming. Rockset supplied a few metrics to illustrate this. For starters, revenue grew 290% in the last quarter. While they didn’t provide any foundational numbers for that percentage growth, it is obviously substantial.

In addition, the startup reports adding hundreds of new users, again not nailing down any specific numbers, and queries on the platform are up 313%. Without specifics, it’s hard to know what that means, but that seems like healthy growth for an early stage startup, especially in this economy.

Mike Vernal, a partner at Sequoia, sees a company helping to get data to work faster than other solutions, which require a lot of handling first. “Rockset, with its innovative new approach to indexing data, has quickly emerged as a true leader for real-time analytics in the cloud. I’m thrilled to partner with the company through its next phase of growth,” Vernal said in a statement.

The company was founded in 2016 by the creators of RocksDB. The startup had previously raised a $3 million seed round when they launched the company and the $18.5 million A round in 2018.

Oct
27
2020
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SimilarWeb raises $120M for its AI-based market intelligence platform for sites and apps

Israeli startup SimilarWeb has made a name for itself with an AI-based platform that lets sites and apps track and understand traffic not just on their own sites, but those of its competitors. Now, it’s taking the next step in its growth. The startup has raised $120 million, funding it will use to continue expanding its platform both through acquisitions and investing in its own R&D, with a focus on providing more analytics services to larger enterprises alongside its current base of individuals and companies of all sizes that do business on the web.

But not, it seems, necessarily an IPO at the moment.

“We will pursue whatever we feel is necessary to grow, so that decision will come from delivering value, not chasing an IPO,” Or Offer, SimilarWeb’s founder and CEO, said in an interview.

Co-led by ION Crossover Partners and Viola Growth, the round doubles the total amount that the startup has raised to date to $240 million. Offer said that it was not disclosing its valuation this time around except to say that his company is now “playing in the big pool.” It counts more than half of the Fortune 100 as customers, with Walmart, P&G, Adidas and Google, among them.

For some context, it hit an $800 million valuation in its last equity round, in 2017.

SimilarWeb’s technology competes with other analytics and market intelligence providers ranging from the likes of Nielsen and ComScore through to the Apptopias of the world in that, at its most basic level, it provides a dashboard to users that provides insights into where people are going on desktop and mobile. Where it differs, Offer said, is in how it gets to its information, and what else it’s doing in the process.

For starters, it focuses not just how many people are visiting, but also a look into what is triggering the activity — the “why”, as it were — behind the activity. Using a host of AI tech such as machine learning algorithms and deep learning — like a lot of tech out of Israel, it’s being built by people with deep expertise in this area — Offer says that SimilarWeb is crunching data from a number of different sources to extrapolate its insights.

He declined to give much detail on those sources but told me that he cheered the arrival of privacy gates and cookie lists for helping ferret out, expose and sometimes eradicate some of the more nefarious “analytics” services out there, and said that SimilarWeb has not been affected at all by that swing to more data protection, since it’s not an analytics service, strictly speaking, and doesn’t sniff data on sights in the same way. It’s also exploring widening its data pool, he added:

“We are always thinking about what new signals we could use,” he said. “Maybe they will include CDNs. But it’s like Google with its rankings in search. It’s a never ending story to try to get the highest accuracy in the world.”

The global health pandemic has driven a huge amount of activity on the web this year, with people turning to sites and apps not just for leisure — something to do while staying indoors, to offset all the usual activities that have been cancelled — but for business, whether it be consumers using e-commerce services for shopping, or workers taking everything online and to the cloud to continue operating.

That has also seen a boost of business for all the various companies that help the wheels turn on that machine, SimilarWeb included.

“Consumer behavior is changing dramatically, and all companies need better visibility,” said Offer. “It started with toilet paper and hand sanitizer, then moved to desks and office chairs, but now it’s not just e-commerce but everything. Think about big banks, whose business was 70% offline and is now 70-80% online. Companies are building and undergoing a digital transformation.”

That in turn is driving more people to understand how well their web presence is working, he said, with the basic big question being: “What is my marketshare, and how does that compare to my competition? Everything is about digital visibility, especially in times of change.”

Like many other companies, SimilarWeb did see an initial dip in business, Offer said, and to that end the company has taken on some debt as part of Israel’s Paycheck Protection Program, to help safeguard some jobs that needed to be furloughed. But he added that most of its customers prior to the pandemic kicking off are now back, along with customers from new categories that hadn’t been active much before, like automotive portals.

That change in customer composition is also opening some doors of opportunity for the company. Offer noted that in recent months, a lot of large enterprises — which might have previously used SimilarWeb’s technology indirectly, via a consultancy, for example — have been coming to the company direct.

“We’ve started a new advisory service [where] our own expert works with a big customer that might have more deep and complex questions about the behaviour we are observing. They are questions all big businesses have right now.” The service sounds like a partly-educational effort, teaching companies that are not necessarily digital-first be more proactive, and partly consulting.

New customer segments, and new priorities in the world of business, are two of the things that drove this round, say investors.

“SimilarWeb was always an incredible tool for any digital professional,” said Gili Iohan of ION Crossover Partners, in a statement. “But over the last few months it has become apparent that traffic intelligence — the unparalleled data and digital insight that SimilarWeb offers — is an absolute essential for any company that wants to win in the digital world.”

As for acquisitions, SimilarWeb has historically made these to accelerate its technical march. For example, in 2015 it acquired Quettra to move deeper into mobile analytics and it acquired Swayy to move into content discovery insights (key for e-commerce intelligence). Offer would not go into too much detail about what it has identified as a further target but given that there are quite a lot of companies building tech in this area currently, that there might be a case for some consolidation around bigger platforms to combine some of the features and functionality. Offer said that it was looking at “companies with great data and digital intelligence, with a good product. There are a lot of opportunities right now on the table.”

The company will also be doing some hiring, with the plan to be to add 200 more people globally by January (it has around 600 employees today).

“Since we joined the company three years ago, SimilarWeb has executed a strategic transformation from a general-purpose measurement platform to vertical-based solutions, which has significantly expanded its market opportunity and generated immense customer value,” said Harel Beit-On, Founder and General Partner at Viola Growth, in a statement. “With a stellar management team of accomplished executives, we believe this round positions the company to own the digital intelligence category, and capitalize on the acceleration of the digital era.”

Aug
25
2020
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New Zendesk dashboard delivers customer service data in real time

Zendesk has been offering customers the ability to track customer service statistics for some time, but it has always been a look back. Today, the company announced a new product called Explore Enterprise that lets customers capture that valuable info in real time, and share it with anyone in the organization, whether they have a Zendesk license or not.

While it has had Explore in place for a couple of years now, Jon Aniano, senior VP of product at Zendesk says the new enterprise product is in response to growing customer data requirements. “We now have a way to deliver what we call Live Team Dashboards, which delivers real-time analytics directly to Zendesk users,” Aniano told TechCrunch.

In the days before COVID that meant displaying these on big monitors throughout the customer service center. Today, as we deal with the pandemic, and customer service reps are just as likely to be working from home, it means giving management the tools they need to understand what’s happening in real time, a growing requirement for Zendesk customers as they scale, regardless of the pandemic.

“What we’ve found over the last few years is that our customers’ appetite for operational analytics is insatiable, and as customers grow, as customer service needs get more complex, the demands on a contact center operator or customer service team are higher and higher, and teams really need new sets of tools and new types of capabilities to meet what they’re trying to do in delivering customer service at scale in the world,” Aniano told TechCrunch.

One of the reasons for this is the shift from phone and email as the primary ways of accessing customer service to messaging tools like WhatsApp. “With the shift to messaging, there are new demands on contact centers to be able to handle real-time interactions at scale with their customers,” he said.

In order to meet that kind of demand, it requires real-time analytics that Zendesk is providing with this announcement. This arms managers with the data they need to put their customer service resources where they are needed most in the moment in real time.

But Zendesk is also giving customers the ability to share these statistics with anyone in the company. “Users can share a dashboard or historical report with anybody in the company regardless of whether they have access to Zendesk. They can share it in Slack, or they can embed a dashboard anywhere where other people in the company would like to have access to those metrics,” Aniano explained.

The new service will be available starting on August 31 for $29 per user per month.

Aug
06
2020
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Mode raises $33M to supercharge its analytics platform for data scientists

Data science is the name of the game these days for companies that want to improve their decision making by tapping the information they are already amassing in their apps and other systems. And today, a startup called Mode Analytics, which has built a platform incorporating machine learning, business intelligence and big data analytics to help data scientists fulfill that task, is announcing $33 million in funding to continue making its platform ever more sophisticated.

Most recently, for example, the company has started to introduce tools (including SQL and Python tutorials) for less technical users, specifically those in product teams, so that they can structure queries that data scientists can subsequently execute faster and with more complete responses — important for the many follow-up questions that arise when a business intelligence process has been run. Mode claims that its tools can help produce answers to data queries in minutes.

This Series D is being led by SaaS specialist investor H.I.G. Growth Partners, with previous investors Valor Equity Partners, Foundation Capital, REV Venture Partners and Switch Ventures all participating. Valor led Mode’s Series C in February 2019, while Foundation and REV respectively led its A and B rounds.

Mode is not disclosing its valuation, but co-founder and CEO Derek Steer confirmed in an interview that it was “absolutely” an up-round.

For some context, PitchBook notes that last year its valuation was $106 million. The company now has a customer list that it says covers 52% of the Forbes 500, including Anheuser-Busch, Zillow, Lyft, Bloomberg, Capital One, VMware and Conde Nast. It says that to date it has processed 830 million query runs and 170 million notebook cell runs for 300,000 users. (Pricing is based on a freemium model, with a free “Studio” tier and Business and Enterprise tiers priced based on size and use.)

Mode has been around since 2013, when it was co-founded by Steer, Benn Stancil (Mode’s current president) and Josh Ferguson (initially the CTO and now chief architect).

Steer said the impetus for the startup came out of gaps in the market that the three had found through years of experience at other companies.

Specifically, when all three were working together at Yammer (they were early employees and stayed on after the Microsoft acquisition), they were part of a larger team building custom data analytics tools for Yammer. At the time, Steer said Yammer was paying $1 million per year to subscribe to Vertica (acquired by HP in 2011) to run it.

They saw an opportunity to build a platform that could provide similar kinds of tools — encompassing things like SQL Editors, Notebooks and reporting tools and dashboards — to a wider set of users.

“We and other companies like Facebook and Google were building analytics internally,” Steer recalled, “and we knew that the world wanted to work more like these tech companies. That’s why we started Mode.”

All the same, he added, “people were not clear exactly about what a data scientist even was.”

Indeed, Mode’s growth so far has mirrored that of the rise of data science overall, as the discipline of data science, and the business case for employing data scientists to help figure out what is “going on” beyond the day to day, getting answers by tapping all the data that’s being amassed in the process of just doing business. That means Mode’s addressable market has also been growing.

But even if the trove of potential buyers of Mode’s products has been growing, so has the opportunity overall. There has been a big swing in data science and big data analytics in the last several years, with a number of tech companies building tools to help those who are less technical “become data scientists” by introducing more intuitive interfaces like drag-and-drop features and natural language queries.

They include the likes of Sisense (which has been growing its analytics power with acquisitions like Periscope Data), Eigen (focusing on specific verticals like financial and legal queries), Looker (acquired by Google) and Tableau (acquired by Salesforce).

Mode’s approach up to now has been closer to that of another competitor, Alteryx, focusing on building tools that are still aimed primarily at helping data scientists themselves. You have any number of database tools on the market today, Steer noted, “Snowflake, Redshift, BigQuery, Databricks, take your pick.” The key now is in providing tools to those using those databases to do their work faster and better.

That pitch and the success of how it executes on it is what has given the company success both with customers and investors.

“Mode goes beyond traditional Business Intelligence by making data faster, more flexible and more customized,” said Scott Hilleboe, managing director, H.I.G. Growth Partners, in a statement. “The Mode data platform speeds up answers to complex business problems and makes the process more collaborative, so that everyone can build on the work of data analysts. We believe the company’s innovations in data analytics uniquely position it to take the lead in the Decision Science marketplace.”

Steer said that fundraising was planned long before the coronavirus outbreak to start in February, which meant that it was timed as badly as it could have been. Mode still raised what it wanted to in a couple of months — “a good raise by any standard,” he noted — even if it’s likely that the valuation suffered a bit in the process. “Pitching while the stock market is tanking was terrifying and not something I would repeat,” he added.

Given how many acquisitions there have been in this space, Steer confirmed that Mode too has been approached a number of times, but it’s staying put for now. (And no, he wouldn’t tell me who has been knocking, except to say that it’s large companies for whom analytics is an “adjacency” to bigger businesses, which is to say, the very large tech companies have approached Mode.)

“The reason we haven’t considered any acquisition offers is because there is just so much room,” Steer said. “I feel like this market is just getting started, and I would only consider an exit if I felt like we were handicapped by being on our own. But I think we have a lot more growing to do.”

Jul
14
2020
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Google Cloud’s new BigQuery Omni will let developers query data in GCP, AWS and Azure

At its virtual Cloud Next ’20 event, Google today announced a number of updates to its cloud portfolio, but the private alpha launch of BigQuery Omni is probably the highlight of this year’s event. Powered by Google Cloud’s Anthos hybrid-cloud platform, BigQuery Omni allows developers to use the BigQuery engine to analyze data that sits in multiple clouds, including those of Google Cloud competitors like AWS and Microsoft Azure — though for now, the service only supports AWS, with Azure support coming later.

Using a unified interface, developers can analyze this data locally without having to move data sets between platforms.

“Our customers store petabytes of information in BigQuery, with the knowledge that it is safe and that it’s protected,” said Debanjan Saha, the GM and VP of Engineering for Data Analytics at Google Cloud, in a press conference ahead of today’s announcement. “A lot of our customers do many different types of analytics in BigQuery. For example, they use the built-in machine learning capabilities to run real-time analytics and predictive analytics. […] A lot of our customers who are very excited about using BigQuery in GCP are also asking, ‘how can they extend the use of BigQuery to other clouds?’ ”

Image Credits: Google

Google has long said that it believes that multi-cloud is the future — something that most of its competitors would probably agree with, though they all would obviously like you to use their tools, even if the data sits in other clouds or is generated off-platform. It’s the tools and services that help businesses to make use of all of this data, after all, where the different vendors can differentiate themselves from each other. Maybe it’s no surprise then, given Google Cloud’s expertise in data analytics, that BigQuery is now joining the multi-cloud fray.

“With BigQuery Omni customers get what they wanted,” Saha said. “They wanted to analyze their data no matter where the data sits and they get it today with BigQuery Omni.”

Image Credits: Google

He noted that Google Cloud believes that this will help enterprises break down their data silos and gain new insights into their data, all while allowing developers and analysts to use a standard SQL interface.

Today’s announcement is also a good example of how Google’s bet on Anthos is paying off by making it easier for the company to not just allow its customers to manage their multi-cloud deployments but also to extend the reach of its own products across clouds. This also explains why BigQuery Omni isn’t available for Azure yet, given that Anthos for Azure is still in preview, while AWS support became generally available in April.

May
27
2020
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RudderStack raises $5M seed round for its open-source Segment competitor

RudderStack, a startup that offers an open-source alternative to customer data management platforms like Segment, today announced that it has raised a $5 million seed round led by S28 Capital. Salil Deshpande of Uncorrelated Ventures and Mesosphere/D2iQ co-founder Florian Leibert (through 468 Capital) also participated in this round.

In addition, the company also today announced that it has acquired Blendo, an integration platform that helps businesses transform and move data from their data sources to databases.

Like its larger competitors, RudderStack helps businesses consolidate all of their customer data, which is now typically generated and managed in multiple places — and then extract value from this more holistic view. The company was founded by Soumyadeb Mitra, who has a Ph.D. in database systems and worked on similar problems previously when he was at 8×8 after his previous startup, MairinaIQ, was acquired by that company.

Mitra argues that RudderStack is different from its competitors thanks to its focus on developers, its privacy and security options and its focus on being a data warehouse first, without creating yet another data silo.

“Our competitors provide tools for analytics, audience segmentation, etc. on top of the data they keep,” he said. “That works well if you are a small startup, but larger enterprises have a ton of other data sources — at 8×8 we had our own internal billing system, for example — and you want to combine this internal data with the event stream data — that you collect via RudderStack or competitors — to create a 360-degree view of the customer and act on that. This becomes very difficult with the SaaS-hosted data model of our competitors — you won’t be sending all your internal data to these cloud vendors.”

Part of its appeal, of course, is the open-source nature of RudderStack, whose GitHub repository now has more than 1,700 stars for the main RudderStack server. Mitra credits getting on the front page of HackerNews for its first sale. On that day, it received over 500 GitHub stars, a few thousand clones and a lot of signups for its hosted app. “One of those signups turned out to be our first paid customer. They were already a competitor’s customer, but it wasn’t scaling up so were looking to build something in-house. That’s when they found us and started working with us,” he said.

Because it is open source, companies can run RudderStack anyway they want, but like most similar open-source companies, RudderStack offers multiple hosting options itself, too, that include cloud hosting, starting at $2,000 per month, with unlimited sources and destination.

Current users include IFTTT, Mattermost, MarineTraffic, Torpedo and Wynn Las Vegas.

As for the Blendo acquisition, it’s worth noting that the company only raised a small amount of money in its seed round. The two companies did not disclose the price of the acquisition.

“With Blendo, I had the opportunity to be part of a great team that executed on the vision of turning any company into a data-driven organization,” said Blendo founder Kostas Pardalis, who has joined RudderStack as head of Growth. “We’ve combined the talented Blendo and RudderStack teams together with the technology that both companies have created, at a time when the customer data market is ripe for the next wave of innovation. I’m excited to help drive RudderStack forward.”

Mitra tells me that RudderStack acquired Blendo instead of building its own version of this technology because “it is not a trivial technology to build — cloud sources are really complicated and have weird schemas and API challenges and it would have taken us a lot of time to figure it out. There are independent large companies doing the ETL piece.”

Apr
22
2020
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Fishtown Analytics raises $12.9M Series A for its open-source analytics engineering tool

Philadelphia-based Fishtown Analytics, the company behind the popular open-source data engineering tool dbt, today announced that it has raised a $12.9 million Series A round led by Andreessen Horowitz, with the firm’s general partner Martin Casado joining the company’s board.

“I wrote this blog post in early 2016, essentially saying that analysts needed to work in a fundamentally different way,” Fishtown founder and CEO Tristan Handy told me, when I asked him about how the product came to be. “They needed to work in a way that much more closely mirrored the way the software engineers work and software engineers have been figuring this shit out for years and data analysts are still like sending each other Microsoft Excel docs over email.”

The dbt open-source project forms the basis of this. It allows anyone who can write SQL queries to transform data and then load it into their preferred analytics tools. As such, it sits in-between data warehouses and the tools that load data into them on one end, and specialized analytics tools on the other.

As Casado noted when I talked to him about the investment, data warehouses have now made it affordable for businesses to store all of their data before it is transformed. So what was traditionally “extract, transform, load” (ETL) has now become “extract, load, transform” (ELT). Andreessen Horowitz is already invested in Fivetran, which helps businesses move their data into their warehouses, so it makes sense for the firm to also tackle the other side of this business.

“Dbt is, as far as we can tell, the leading community for transformation and it’s a company we’ve been tracking for at least a year,” Casado said. He also argued that data analysts — unlike data scientists — are not really catered to as a group.

Before this round, Fishtown hadn’t raised a lot of money, even though it has been around for a few years now, except for a small SAFE round from Amplify.

But Handy argued that the company needed this time to prove that it was on to something and build a community. That community now consists of more than 1,700 companies that use the dbt project in some form and over 5,000 people in the dbt Slack community. Fishtown also now has over 250 dbt Cloud customers and the company signed up a number of big enterprise clients earlier this year. With that, the company needed to raise money to expand and also better service its current list of customers.

“We live in Philadelphia. The cost of living is low here and none of us really care to make a quadro-billion dollars, but we do want to answer the question of how do we best serve the community,” Handy said. “And for the first time, in the early part of the year, we were like, holy shit, we can’t keep up with all of the stuff that people need from us.”

The company plans to expand the team from 25 to 50 employees in 2020 and with those, the team plans to improve and expand the product, especially its IDE for data analysts, which Handy admitted could use a bit more polish.

Mar
06
2020
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Oribi brings its web analytics platform to the US

Oribi, an Israeli startup promising to democratize web analytics, is now launching in the United States.

While we’ve written about a wide range of new or new-ish analytics companies, founder and CEO Iris Shoor said that most of them aren’t built for Oribi’s customers.

“A lot of companies are more focused on the high end,” Shoor told me. “Usually these solutions are very much based on a lot of technical resources and integrations — these are the Mixpanels and Heap Analytics and Adobe Marketing Clouds.”

She said that Oribi, on the other hand, is designed for small and medium businesses that don’t have large technical teams: “They have digital marketing strategies that are worth a few hundred thousand dollars a month, they have very large activity, but they don’t have a team for it. And I would say that all of them are using Google Analytics.”

Shoor described Oribi as designed specifically “to compete with Google Analytics” by allowing everyone on the team to get the data they need without requiring developers to write new code for every event they want to track.

Event Correlations

In fact, if you use Oribi’s plugins for platforms like WordPress and Shopify, there’s no coding at all involved in the process. Apparently, that’s because Oribi is already tracking every major event in the customer journey. It also allows the team to define the conversion goals that they want to focus on — again, with no coding required.

Shoor contrasted Oribi with analytics platforms that simply provide “more and more data” but don’t help customers understand what to do with that data.

“We’ve created something that is much more clean,” she said. “We give them insights of what’s working; in the background, we create all these different queries and correlations about which part of the funnels are broken and where they can optimize.”

There are big businesses using Oribi already — including Audi, Sony and Crowne Plaza — but the company is now turning its attention to U.S. customers. Shoor said Oribi isn’t opening an office in the United States right away, but there are plans to do so in the next year.

Sep
18
2019
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Tableau update uses AI to increase speed to insight

Tableau was acquired by Salesforce earlier this year for $15.7 billion, but long before that, the company had been working on its fall update, and today it announced several new tools, including a new feature called “Explain Data” that uses AI to get to insight quickly.

“What Explain Data does is it moves users from understanding what happened to why it might have happened by automatically uncovering and explaining what’s going on in your data. So what we’ve done is we’ve embedded a sophisticated statistical engine in Tableau, that when launched automatically analyzes all the data on behalf of the user, and brings up possible explanations of the most relevant factors that are driving a particular data point,” Tableau chief product officer, Francois Ajenstat explained.

He added that what this really means is that it saves users time by automatically doing the analysis for them, and It should help them do better analysis by removing biases and helping them dive deep into the data in an automated fashion.

Explain Data Superstore extreme value

Image: Tableau

Ajenstat says this is a major improvement, in that, previously users would have do all of this work manually. “So a human would have to go through every possible combination, and people would find incredible insights, but it was manually driven. Now with this engine, they are able to essentially drive automation to find those insights automatically for the users,” he said.

He says this has two major advantages. First of all, because it’s AI-driven it can deliver meaningful insight much faster, but also it gives a more rigorous perspective of the data.

In addition, the company announced a new Catalog feature, which provides data bread crumbs with the source of the data, so users can know where the data came from, and whether it’s relevant or trustworthy.

Finally, the company announced a new server management tool that helps companies with broad Tableau deployment across a large organization to manage those deployments in a more centralized way.

All of these features are available starting today for Tableau customers.

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