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About Amalgam Insights

Amalgam Insights is working on a new website experience for you in 2022 to help with your Technology Expense Management, Data and Analytics, and Business Planning Management challenges.

In the meantime, if you need to reach us, please contact Hyoun Park ( or Lisa Lincoln ( We thank you for your patience as we get set up!

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November 12: From BI to AI (Domino,, IBM, Informatica, Tableau)

Product Launches and Enhancements

IBM to Add New Natural Language Processing Enhancements to Watson Discovery

On November 10, IBM revealed new natural language processing enhancements planned for IBM Watson Discovery. Business users will be able to train Watson Discovery to surface insights more quickly on a corpus of industry-specific documents without needing traditional data science skills. Specific capability enhancements include pre-trained document structure understanding, automatic text pattern detection, and a custom entity extractor feature that will help identify industry-specific words and phrases with specific contexts. The announced enhancements are forthcoming, though IBM did not announce a target release date.

Informatica Announces Cloud Data Marketplace

On November 11, Informatica debuted their Cloud Data Marketplace. The Cloud Data Marketplace will allow Informatica business users to “shop” for both datasets and AI and analytics models, surfacing existing assets to encourage reuse of more-vetted resources rather than duplicating efforts by re-gathering data or building a model from scratch. Informatica Cloud Data Marketplace is available today with consumption-based pricing on Informatica’s Intelligent Data Management Cloud.

Tableau Outlines Product Vision and the Future of Analytics at Tableau Conference 2021

On November 9, at Tableau Conference 2021, Tableau announced a host of innovations for the Tableau platform and ecosystem, focused on bringing analytic capabilities to the workflows and environments workers already use. Highlights include Model Builder, a new feature in Tableau Business Science that allows Tableau users to build predictive models using Einstein Discovery; and Scenario Planning, another new Tableau Business Science feature to compare scenarios and “what-ifs,” supported by Einstein AI.


Domino Data Lab Expands Collaboration with NVIDIA and TCS with New Enterprise MLOps Solutions for Modern IT Stacks

On November 9, Domino Data Lab announced a fully-managed offering with solutions partner Tata Consultancy Services that allows Domino customers to run high-performance computing and data science workloads on NVIDIA DGX systems, hosted in the TCS Enterprise Cloud. This marks the next step in a deepening relationship between Domino and NVIDIA, with the Domino integration into the NVIDIA AI Enterprise suite on the horizon.

Funding Closes $100 Million in Funding Led by Customer Commonwealth Bank of Australia

On November 8, closed $100M in Series E funding. The round was led by customer Commonwealth Bank of Australia, with participation by existing investors Crane Venture Partners and Goldman Sachs Asset Management and new investor Pivot Investment Partners. The funding will be used to scale up partnerships, sales, marketing, and customer success at a global level.

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Domino Data Lab Raises $100 Million F Round to Enable the Model-Driven Enterprise

On October 5, Domino Data Lab announced a $100 million F round led by private equity firm Great Hill Partners and joined by existing investors Coatue, Highland Capital, and Sequoia Capital. Domino Data Lab is a company we have covered since the inception of Amalgam Insights in 2017. From the start, it was obvious that Domino Data was designed to support data science teams that sought to manage data science exploration and machine learning outputs with enterprise governance.

This investment is obviously an eye catcher and is in line with other massive rounds that data science and machine learning solutions have been raising, such as DataRobot’s July 2021 G round of $300 million, Dataiku’s August 2021 $400 million round, or Databricks’ gobsmacking August 2021 round of $1.6 billion. In light of these funding rounds, one might be tempted to ask the seemingly absurd question of whether $100 million is enough!

Fortunately, even in these heady economic times, $100 million is still a significant amount of cash to fund growth and the other funding rounds demonstrate that this is a hot market. In addition, Domino Data’s focus on mature data science practices and teams means that the marketing, sales, and product teams can focus on high-value applications for developers and data analysts rather than having to try to be everything for everyone.

In addition, the new lead investor Great Hill Partners is a firm that Amalgam Insights considers “smart money” in that it specializes in investments roughly around this $100 million size with the goal of pushing data-savvy companies beyond the billion dollar valuation. A quick look at Great Hill Partners shows that they have assigned both founder Chris Gaffney and long-time tech executive Derek Schoettle to this investment, both of whom have deep expertise in data and analytics.

With this investment, Amalgam Insights expects that Domino Data will continue to solve a key problem that exists in enterprise machine learning and artificial intelligence: orchestrating and improving models and AI workloads over time. As model creation and hosting have become increasingly simple to initiate, enterprises now face the potential issues of technology debt associated with AI. Effectively, enterprises are replacing “Big Data” issues with “Big Model” issues where the breadth and complexity of models become increasingly difficult to govern and support without oversight and AI strategy. This opportunity cannot be solved through automated model creation or traditional analytic and business intelligence solutions as the combinations of models, workflows, and governance associated with data science require a combination of testing, collaboration, and review that is lacking in standard analytic environments. With mature data science teams now becoming an early majority capability at the enterprise level, Domino Data’s market has now caught up to the product.

Domino Data’s funding announcement also mentioned the launch of a co-selling agreement with NVIDIA. Although this agreement isn’t novel and NVIDIA has a variety of agreements with other software companies, this particular agreement allows NVIDIA and Domino Data to provide both the hardware and software to develop optimized machine learning at scale. Amalgam Insights expects that this agreement will allow enterprises to accelerate their development of machine learning models while providing a management foundation for the ongoing governance and support of data science. Enterprise-grade data science ultimately requires not only the technical capability to deploy a model, but the ability to audit and review models for ongoing improvement or disconnections

From an editorial perspective, it is amazing to see how quickly Domino Data Lab has grown over the past three years. When we first briefed Domino Data in 2017, we frankly stated that the solution was ahead of its time as enterprises typically lacked the formal teamwork and organizational structure to support data science. It wasn’t that businesses shouldn’t have been thinking about data science teams, but rather that IT and analytics teams simply were not keeping up with the state of technology. And in response, Domino Data actually launched a data science framework to define collaborative data science efforts.

Recommendation for Amalgam Insights’ Data and Analytics Community

Funding announcements typically are associated with growth expectations: the bigger the round, the higher the sales and marketing expectations. Domino Data is raising this money now both because it is seen as a market leader in supporting data science and that companies have reached a tipping point in requiring solutions for collaborative and compliant data science management.

Amalgam Insights’ key recommendation based on this funding round as well as recent funding from other vendors is to review current data science capabilities within your organization and ensure that the compliance, governance, and collaborative capabilities are on par with your current analytics, business intelligence, and application development capabilities. The toolkits for collaborative data science have evolved massively over the past couple of years and data science is no longer a task for the “lone-wolf genius” but for an enterprise team expected to provide high-value digital assets. Compare current data science operationalization and management solutions to existing in-house capabilities and conduct a realistic analysis of the time, risk, and total cost of ownership savings associated with each approach. With a mature vendor landscape now in place to help support data science, this is the time for early majority data science adopters to take full advantage of their capabilities over market competitors by creating a mature data science environment and quickly building AI where competitors still depend on manual or static black-box processes.

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Market Alert: NetApp Agrees to Acquire CloudCheckr to Improve Cloud Cost Environments

On October 4th, 2021, NetApp announced a definitive agreement to acquire CloudCheckr, a market leader in cloud financial and operational optimization. NetApp positions this acquisition as accretive to its agreement to acquire Spot (now called Spot by NetApp post-acquistion) in June 2020 to support hybrid cloud optimization and usage management. This Market Alert explains why NetApp agreed to purchase CloudCheckr and provides recommendations for cloud professionals seeking to make a decision on purchasing or evaluating a cloud cost, cloud optimization, or Cloud FinOps (Financial Operations) solution.

About CloudCheckr

CloudCheckr was founded in 2011 in Rochester, New York in the United States as a solution to support the cost management, operational automation, compliance, and security of cloud Infrastructure as a Service. CloudCheckr was founded by Aaron Klein and Aaron Newman, who currently serves as Chairman. Over the past decade, CloudCheckr has gained over $4 billion dollars in spend under management to support over 600 clients and 10,000 employee users.

CloudCheckr raised its first significant round of funding in 2017, when it announced a massive $50 million Series A round from Level Equity. (Note: This acquisition occurred a couple of months before Amalgam Insights was founded, but I covered this announcement at my previous firm.)

This unusually large round of funding was justified by CloudCheckr’s status as a profitable bootstrapped organization with the opportunity to scale in a high growth area. At the time, CloudCheckr had over 150 clients and $1 billion in spend under management, meaning that the organization has grown roughly four times as large over the last four years after this initial round of funding. CloudCheckr also raised a second round of $15 million in 2019 from Level Equity to support product and engineering capabilities around the same time that the firm appointed Tim McKinnon as CEO.

Contextualizing the CloudCheckr Acquisition

Cloud optimization has been a rapidly growing market for several reasons: the IT Rule of 30, the growth of the IaaS market, and the nascent and emerging nature of best practices for managing cloud computing.

First, Amalgam Insights’ IT Rule of 30, which states that every unmanaged IT subcategory averages 30% waste, is definitely true in for Infrastructure as a Service (IaaS), where cloud spend is poorly governed and where end users, procurement, accounting, and finance are rarely working together as a team to manage these costs in a coordinated fashion. From a cloud perspective, this percentage roughly equates to moving from about 50% utilization to 80%+ utilization of provisioned services based on active monitoring of services.

Second, the IaaS market as a whole continues to grow roughly 25% per year as roughly 60% of institutional or enterprise-grade storage and compute is in the cloud rather than an asset-intensive data center investment.

Third, cloud IaaS billing and product deployment are still fairly immature or agile (depending on your point of view) with rapid launches, updates, changes, and obsolescence based on adoption trends and customer requests. From a functional perspective, this rapid change can often provide great value, but it also means that the financial expectations associated with instances can often change without any formal change management, billing review, or contractual review. All of these trends lead to a volatile billing, usage management, and compliance environment that is difficult to manage without a combination of proactive analysis, alerts, and holistic visualization.

How CloudCheckr Augments Spot by NetApp

NetApp’s acquisition of CloudCheckr fits well into the trends of this space and can be seen as part of a trend of acquisitions that includes Apptio’s 2019 acquisition announcement of Cloudability or Flexera’s 2018 acquisition of Rightscale or VMware’s 2018 acquisition of CloudHealth Technologies. All of these acquisitions filled the needs of IT management providers to support multi-cloud management for enterprises and managed service providers seeking to manage large pools of cloud spend and resources. From Amalgam Insights’ perspective, these are still early days for cloud computing as a whole as cloud currently makes up roughly a third of enterprise data infrastructure spend. From a market perspective, AI believes that we are in a period where cloud infrastructure cost management vendors represent growth assets now that multi-cloud best practices are starting to emerge and cloud service providers are treated more along the lines of telecom carriers for services that provide utility pricing and capacity.

At a time when cloud computing is obviously the highest growth area for IT spend, with IaaS spend expected to double every three years for the rest of this decade, IT systems management firms see the complexity of cloud as a fundamental challenge to the ongoing management of cloud services.

This acquisition builds onto existing Spot by Netapp’s capabilities in supporting usage and resource tracking as well as NetApp’s recent acquisition of Data Mechanics to support big data analytics. Although initial press releases and interviews position CloudCheckr as an acquisition to help support Spot by NetApp, Amalgam Insights notes that these two technology solutions are different in nature.

Spot by NetApp excels in providing a software-driven capability for monitoring and optimizing storage and compute infrastructure. This optimization provides a lot of value and can often seen as a be-all and end-all for infrastructure cost management to identify the portfolio of on-demand, reserve, and spot instances used to support infrastructure.

However, experiencted IT expense managers have seen that IT cost management requires a holistic lifecycle approach that involves a combination of usage optimization, service order automation, resource governance, inventory management, multi-cloud sourcing, invoice and payment management, and effective alignment of services with business-driven demand. This level of analysis requires a view into the products, cost centers, projects, and comparative cloud usage patterns that may require changing services and providers or using alternative billing approaches such as setting up reserved instances or savings plans for ongoing operationalization.

At the same time, cost management in the cloud is also often related to managing access and governance associated with existing resources. A basic example of this issue is Amazon S3 bucket governance, which can both be a security issue as well as a potential cost issue based on what is placed within the bucket.

Recommendations for the Cloud, FinOps, and NetApp Communities

As we consider this acquisition, it is important for us to not simply recommend a purchase, but to provide a course of action that will help IT departments to optimize their cloud environments. Based on this acquisition, Amalgam Insights provides the following recommendations based on our experience in tracking cloud cost and Kubernetes cost management over the past four years.

  1. To manage cloud costs, resource optimization is just the starting point. To fully tackle the IT Rule of 30 and regain all of the misplaced IT costs created in less governed times, it is important to make sure that all orders are governed with business logic. The goal here is not to prevent developers from quickly building but to make sure that every service is accounted for, effectively governed, and disconnected in a timely and appropriate manner. From a practical perspective, this monitoring requires some level of centralization that allows all developers and architects to have a shared version of the truth and a consistent inventory that brings together all accounts and services used by IT.
  2. For CloudCheckr customers, this acquisition provides an opportunity to take advantage of the Spot by NetApp cost optimization capability, especially in selecting spot instances that can greatly reduce the cost of managing standard cloud workloads. This spot management capability requires a combination of process modeling and price monitoring that is typically outside the core skills of cloud architects or IT expense professionals that are looking at cloud costs.
  3. For Spot by NetApp customers, consider both the value of presenting cloud costs for accounting and finance audiences as well as the power of governing resources to drive additional cost savings and increase the maturity of treating cloud as a strategic business resource. These are capabilities that CloudCheckr provides for enterprise cloud environments. From a practical perspective, IT departments should check and see if they have already covered these important aspects of cloud management either with homegrown or other third-party solutions. Amalgam Insights recommends that organizations that have not filled these gaps should consider adopting CloudCheckr capabilities.
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Zoom, Five9 Call Off the Wedding: What’s Next?

Reluctant shareholders have put the kibosh on Zoom’s intention to buy contact-center-as-a-service provider Five9. The deal would have amounted to almost $15 billion. 

But it was an all-stock deal. As it turns out, Five9 shareholders weren’t such fans of that structure. Zoom’s stock has declined 25% since the video conferencing behemoth announced in July it would buy Five9. Those share prices were not shaping up in Five9 investors’ favor. So, on Sept. 30, they voted against Zoom’s proposed, $14.7 billion purchase. As a result, Zoom and Five9 announced they had mutually terminated the acquisition.

Zoom had sought out Five9 for its cloud contact center expertise. Throughout the pandemic, organizations worldwide have relied on Zoom to keep their teams intact through video conferencing. To help users through uncertain times, Zoom has understood that it needs to deliver even more functional and appealing features, and it made good at Zoomtopia 2021. Part of its new platform announcements included the Video Engagement Center, which contains important contact center capabilities. Notably, though, Zoom debuted that component separate from any Five9 announcements. Did the company see Five9 shareholder rejection coming two weeks later or was it already planning to incorporate Five9 into its VEC portfolio? Either way, the answer might not matter much. Zoom and Five9 say they will still work together.

“We will continue to partner with Zoom like we did before, and just as we partner with other UC providers like Microsoft Teams, Nextiva, Mitel, and others,” Five9 told analysts in an Oct. 1 statement. “This allows us to offer customers the choice they often crave when looking at building out their [customer experience] ecosystem.”

Zoom CEO Eric Yuan said his company will “maintain our valued existing contact center partnerships with companies like Five9, Genesys, NICE inContact, Talkdesk, and Twilio.” 

Amalgam Insights believes Five9 did indeed present Zoom with an attractive acquisition target. The 20-year-old Five9 stands out as a pioneer in cloud contact center. It was among the first contact center developers to understand the need for multimodal chat — not just phone conversations, which often frustrate users enduring iffy interactive voice response, but giving agents and customers the ability to communicate over email, social media, chat function, and text. It also homed in on the importance of easy-to-access analytics to help improve the customer experience in real-time. Combining Zoom and Five9 would have added more heft to Zoom’s offerings. Nonetheless, for its part, Five9 is doing just fine on its own as a standalone public company (fluctuating stock prices notwithstanding); it boasts a $10.6 billion market capitalization. While a union between it and Zoom would have created a global giant, both companies can fuel success by partnering with one another — again, as they say they will do. 

Even so, Zoom needs to diversify. The company tripled its value over the past two years, thanks in no small part to COVID-19. Demand for its services led to an extra $50 billion (and counting) in its market cap and spending power. Now is the time for Zoom to prove it can hold onto, and keep powering, its dominant position. For sure, the company made waves at its Zoomtopia 2021 event in mid-September, giving Amalgam Insights analysts reason to predict the video conferencing provider is aware of the mandate in front of it. Zoom debuted much-needed enhancements — from live translation and transcription and Smart Gallery improvements to hot desking and events hosting — that promise to make video conferencing far more than a pandemic-related enabler. Zoom appears to be hyperfocused on innovation.

Still, if it decided to renegotiate a Five9 purchase with cash replacing some stock, the pairing would make a natural fit despite a first failed attempt. If that doesn’t happen, Zoom should keep an eye out for other unified communications and contact center players that would beef up its platform in unique ways. Five9, meanwhile, may be courted by the likes of Salesforce or Adobe as the contact center becomes an even more ferocious battleground for supporting customer centricity. Both of those companies are high on the list of vendors needing to augment their video conferencing platforms with differentiated integrations, and both have deep pockets.

Overall, even if Zoom does not retool its bid, or if Five9 moves on to greener pastures, both Zoom and Five9 must stay trained on the future. Hybrid work represents the next major paradigm for organizations, and it’s a challenging one for them to navigate. They have to accommodate in-office and remote workers, and many of those people will flow between the two modes. This calls for stringent attention to concerns including data protection, yet requires easy-to-use tools and omnipresent support for the shifts between in-person and at-home working. The vendors that make hybrid work simple and smooth are the ones that will prevail. As Zoom continues its mission to “make video communications frictionless and secure,” it must continue to lead both with the innovation and flexibility that made it a surprise hit in 2020. And regardless of whether Five9 is acquired or remains an independent vendor, the demand for omnichannel and preferred channel support will stick. As such, Five9 will keep evolving cutting-edge technologies to improve the state of customer interaction.

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August 20: From BI to AI (Adapdix, Apollo GraphQL, Cloudera, Databricks, Edge Intelligence, Monte Carlo, SnapLogic, TigerGraph)

If you would like your announcement to be included in Amalgam Insights’ weekly data and analytics roundups, please email

Product Launches and Updates

Cloudera Introduces Cloudera DataFlow for the Public Cloud

On August 16, Cloudera launched Cloudera DataFlow for the Public Cloud to better manage customer data flows. When too many data flows are deployed into a single cluster, performance often falters, yet choosing larger infrastructure footprints “just in case” is expensive. Cloudera DataFlow was created to automate and manage complex cloud-native data flow operations, automatically scale up and down said streaming data flows more efficiently, and cut customers’ cloud costs. Cloudera DataFlow is generally available on AWS now.

Latest Release of the SnapLogic Platform: Self-service Integration and Automation

On August 17, SnapLogic announced its August 2021 product release, introducing no-code SnapLogic Flows for business users, ELT support to Databricks’ Delta Lake, and zero downtime upgrades, along with updating its API lifecycle and development portal. SnapLogic Flows will enable business users to construct data flows and apps to integrate into popular business software such as Salesforce without needing to know how to code, while allowing IT to provide guiderails and requirements to oversee said apps. New features in SnapLogic API lifecycle management include the abilities to maintain, improve, unpublish, deprecate, and retire APIs, ensuring that older versions aren’t used in error.


Apollo GraphQL Announces $130 Million Series D Investment to Power the Future of Graph and Application Development

On August 17, Apollo GraphQL announced a $130M Series D funding round. Insight Partners led the round, with participation from existing funders Andreessen Horowitz, Matrix Partners, and Trinity Ventures, and new investor Next47. The funding will be used on continuing R+D of open source graph technology to make app development faster and more accessible.

Monte Carlo Raises Series C, Brings Funding to $101M to Help Companies Trust Their Data

On August 17, Monte Carlo, a data reliability company, announced a $60M Series C funding round, led by ICONIQ Growth. Salesforce Ventures, along with existing investors Accel, GGV Capital, and Redpoint Ventures, all participated. Monte Carlo will use the funds to expand its product offerings, support more use cases, and open up to new markets.


Adapdix acquires Edge Intelligence to bring data and AI closer together

Adapdix, an edge AI/ML platform, announced the acquisition of Edge Intelligence, a data management platform, on August 16. Edge Intelligence will improve Adapdix’ existing EdgeOps Data Mesh with better data management capabilities, and allow Adapdix to expand its existing offerings in edge automation.


Fermín Serna Joins Databricks as Chief Security Officer

On August 19, Databricks announced that they had appointed Fermín Serna as the company’s new Chief Security Officer. Serna is coming over from Citrix, where he was the Chief Information Security Officer; before this, Serna was the Head of Product Security at Google. At Databricks, Serna will lead the network, platform and user security programs, as well as governance and compliance efforts.

TigerGraph Adds Industry Leader and Trailblazer to its Executive Team; Announces Fall Graph + AI Summits

On August 19, TigerGraph, a graph analytics platform, announced that they had hired Dr. Jay Yu as Vice President of Product Innovation, and as GM at the San Diego Innovation Center for TigerGraph. Dr. Yu comes to TigerGraph from 18 years at Intuit, where he led the Financial Knowledge Graph project and encouraged graph technology adoption in large commercial cases. TigerGraph also announced the Graph + AI Summit for this fall on two dates, October 5 in San Francisco and October 19th in New York. Both hybrid events will be livestreamed to virtual attendees, as well as including in-person attendance.

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August 13: From BI to AI (DataRobot, Mindtech, NodeGraph, Oracle, Qlik, Snorkel AI, Talend)


Snorkel AI Raises $85 Million at $1 Billion Valuation for Data-Centric AI

On August 9, Snorkel AI, a programmatic data labeling platform, snagged an $85M Series C round at a $1B valuation. Addition and various BlackRock funds and accounts led the round, with participation from previous investors Greylock, GV, Lightspeed Venture Partners, Nepenthe Capital, and Walden. The funding will go towards scaling Snorkel AI’s engineering team and growing its go-to-market team for global sales.

Product Launches and Updates

Mindtech Chameleon 21.1

On August 11, Mindtech announced updates to Chameleon, their synthetic image creation and curation platform for training visual AI systems. Data scientists and machine learning engineers will be able to create the exact annotated images they need to train their visual AI models. Key new features and enhancements include Simulator, which uses real-world behavior modeling to create synthetic data sets, and Curation Manager, which performs visual analysis of synthetic and real datasets to identify diversity and bias. Chameleon 21.1 is available for immediate licensing.

Oracle Announces MySQL Autopilot for MySQL HeatWave Service

On August 10, Oracle announced MySQL Autopilot, a new component of Oracle’s MySQL HeatWave service. Autopilot automates HeatWave, a MySQL query acceleration engine in the Oracle cloud, by building machine learning models to help it learn how to perform optimally. Oracle also debuted MySQL Scale-out Data Management at the same time to improve the performance of reloading data into HeatWave by 100x.

Talend Announces Latest Innovations to Support Journey to Healthier Data

On August 11, Talend announced updates to Talend Data Fabric, its data integration and governance platform. Key innovations include native integration with Databricks 7.3 and AWS EMR 6.2 on Apache Spark 3 to enable faster advanced analytics at scale, private connectivity between Talend and AWS or Azure to support HIPAA and PCI compliance, and adding read/write capabilities to a campaign directly from a data pipeline.


Qlik Acquires NodeGraph To Enhance End-to-End Analytics Data Pipelines With Interactive Data Lineage and Drive ‘Explainable BI’

On August 12, Qlik acquired NodeGraph, a metadata management platform. NodeGraph’s interactive data lineage function will contribute to Qlik’s “explainable BI” capabilities, while the governance aspects will enhance the Qlik data fabric, and NodeGraph’s impact analysis capabilities will expand Qlik’s SaaS offerings.


Customer-Focused C-Suite Appointments Bolster DataRobot’s Executive Leadership Team

On August 12, DataRobot welcomed three new appointments to their C-Suite. Jay Schuren moves up as DataRobot’s first Chief Data Science Officer, having come over in 2017 with the Nutonian acquisition. Sirisha Kadamalakalva joined DataRobot as their first Chief Strategy Officer from Bank of America, where she was the Managing Director and Global Head of AI/ML, Analytics, and CRM Software Investment Banking. Steve Jenner came over from Zscaler, where he was the Vice President of Worldwide Sales Engineering.

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August 6: From BI to AI (Ahana, Alteryx, Dataiku, Exadel, MuleSoft, PwC, ServiceNow, Servicetrace, Snowflake, Spell, Swarm64)

If you would like your announcement to be included in Amalgam Insights’ weekly data and analytics roundups, please email


Dataiku Raises $400M at a $4.6B Valuation to Enable Everyday AI in the Enterprise

On August 5, Dataiku announced that they had raised $400M in a Series E round of funding. Tiger Global led the round, with participation from existing investors Battery Ventures, CapitalG, Dawn Capital, FirstMark Capital, ICONIQ Growth, and Snowflake Ventures, as well as new investors Eurazeo, Insight Partners, and Lightrock.

Presto Company Ahana Raises $20M Series A Led By Third Point Ventures To Redefine Open Data Lake Analytics

On August 3, Ahana announced a $20M series A funding round. Third Point Ventures led the round, with participation from GV, Leslie Ventures, and Lux Capital. In addition, Robert Schwartz, a Managing Partner at Third Point Ventures, will join Ahana’s Board of Directors. With the funding, Ahana will accelerate engineering and contributions to the open source data lake analytics Presto project, and expand its go-to-market team.

Product Launches and Updates

Spell Operationalizes Advanced AI with Comprehensive MLOps Platform for Deep Learning

On August 4, Spell launched the eponymous Spell, an MLOps platform for deep learning. The goal is to reduce the cost of operationalizing complex deep learning models that use natural language processing, machine vision, voice recognition, and other similarly complex models dependent on deep learning.

Exadel’s Open Source Face Recognition Application CompreFace Adds New Features

On August 3, Exadel announced improvements to CompreFace, their open source facial recognition application. The updates include additional services and plugins such as face detection and verification, age and gender detection, support for the facial recognition library InsightFace, an improved user experience, added scalability and GPU support, and JavaScript and Python SDKs to make integration easier.

Acquisitions and Partnerships

Alteryx becomes Elite partner in the Snowflake Partner Network to Further Accelerate Analytics and Data Science Automation for Global Organizations

Alteryx made an additional partnership announcement at the end of last week around their efforts to address analytics automation; given the context of the automation acquisitions announced this week, it’s worth mentioning as part of a larger trend. In addition to the BluePrism and PwC announcements, Alteryx has become an Elite Technology Partner in the Snowflake ecosystem, building on the deeper relationship announced in June and reflecting a growing number of Alteryx-Snowflake users working on automated analytics projects.

MuleSoft enters agreement to acquire Servicetrace

On August 2, Salesforce announced their intent to acquire Servicetrace, an RPA provider, and to integrate it into their MuleSoft data integration platform. In particular, Servicetrace’s capabilities will enhance Salesforce’s Einstein Automate, empowering additional workflow automation for Salesforce customers.

ServiceNow to acquire Swarm64 to support the world’s largest workflows

On August 5, ServiceNow announced their intent to acquire Swarm64, a database performance company. Once Swarm64 has been integrated into ServiceNow’s solutions, customers will be able to query their data sources more quickly as part of the workflows they build with ServiceNow’s Now Platform, in addition to working with larger datasets.

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Now Available: The CIO’s Guide for Managing Wireless Expenses in 2021

Amalgam Insights has just published the definitive guide to managing the financial aspects of enterprise mobility in our new report “CIO’s Guide for Managing Wireless Expenses for 2021.” This report, co-authored by Chief Analyst Hyoun Park and Senior Research Analyst Kelly Teal focuses on

  • managing mobility in the New Normal of the hybrid workplace
  • identifying what is differentiated and what is not in the wireless expense world
  • why your mobility costs have risen faster than expected, especially if you took the advice of certain research firms that misread COVID
  • and the 15 vendors that Amalgam Insights recommends that mid-sized and large businesses consider based on their cost management and mobility management needs.

This report is available at

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July 30: From BI to AI (Algorithmia, Alteryx, Atos, AtScale, Blue Prism, DataRobot, Domino Data Lab, EZOPS, Google Cloud, IBM, Informatica, Kili Technologies, Kyndryl, PwC, SAP, SAS, Trifacta, Visual BI)

If you would like your announcement to be included in these data platform-focused roundups, please email


DataRobot Unveils Major Milestones, Including $300M Series G Funding Investment

On July 27, DataRobot announced a $300M Series G funding round. Repeat investors Altimeter Capital and Tiger Global led the round, along with participation from new investors Counterpoint Global (Morgan Stanley), Franklin Templeton, ServiceNow Ventures, and Sutter Hill Ventures. The funding will be used for further development of DataRobot’s Augmented Intelligence platform, as well as expanding its go-to-market team.

Kili Technology raises $25M Series A

Also on July 27, Kili Technology revealed that it had raised a $25M Series A funding round. Balderton Capital led the round. The company is looking to accelerate hiring with the funding.

SAS charts path to IPO-readiness

On July 29, SAS announced that it intended to be ready for an IPO by 2024. Key steps SAS will take over the next couple of years include refining its financial reporting structure, optimizing certain operational processes, and further developing its AI and analytics capabilities.

Acquisitions and Partnerships

Alteryx and PwC Expand Strategic Relationship Globally to Address Analytics Automation Demand

Blue Prism Partners with Alteryx to Drive Faster, More Reliable Data Analytics

Alteryx revealed news about two partnerships this week. On July 28, Alteryx announced a new partnership with Blue Prism, an intelligent automation company, along with a bi-directional integration between the two platforms. Blue Prism developers will be able to include Alteryx analytic processes within RPA-driven processes, while Alteryx analysts will be able to trigger Blue Prism digital workers from within their Alteryx workflows.

On July 29, Alteryx announced that it was expanding its relationship with PwC. The original partnership, announced in February 2020, focused on upskilling and digital transformation efforts in US companies; these efforts are now being expanded globally.

Atos acquires Visual BI to enhance its ability to address customers’ increasing need for analytics in the cloud

On July 29, Atos, a digital transformation company, announced that it was acquiring Visual BI, a cloud data analytics company. By acquiring Visual BI, Atos hopes to address its customers’ increasing need for cloud-based BI and analytics.

DataRobot is Acquiring Algorithmia, Enhancing Leading MLOps Architecture for the Enterprise

The same day it announced $300M in Series G Funding (see above), DataRobot also revealed that it was acquiring MLOps platform Algorithmia.

Domino Data Lab Announces New Partner Network

On July 29, Domino Data Lab debuted the Domino Partner Network, connecting technology and services partners across four categories: Tools & Data, Infrastructure, Solutions, and Implementation & Consulting. Inaugural members include Accenture, AWS, DataArt, Dell Technologies, MathWorks, NetApp, NVIDIA, and Snowflake, among others.

Google Cloud and SAP Partner to Accelerate Business Transformations in the Cloud

IBM and SAP to Help Financial Institutions Accelerate Cloud Adoption to Modernize Operations in a Secured Environment

SAP had two partner announcements this week as well. On July 28, SAP announced that it intends to expand the availability of SAP finance and data management solutions on IBM Cloud for Financial Services, which have built-in security and compliance controls to address financial regulations around risk and data. The goal is to accelerate adoption of IBM Cloud within the financial services industry.

On July 29, SAP and Google Cloud announced that they would be expanding their strategic partnership. Google Cloud will now be a strategic partner for RISE with SAP, SAP’s digital transformation offering. Similar to SAP’s IBM partnership, the goal is to accelerate cloud adoption and business process migration even further.

Product Enhancements

AtScale AI-Link Connects Business Intelligence and Enterprise AI with Semantic Layer to Scale Augmented Analytics and Data Science

On July 29, AtScale introduced AI-Link. AtScale allows BI teams to consume live cloud data with preferred apps; data scientists can now access the same data with Python via AI-Link to put into augmented analytics and machine learning models. AI-Link is available today as an add-on to AtScale.

EZOPS Supports Streamlined Data Control and Optimized Efficiency in Snowflake

On July 27, EZOPS announced that they are incorporating Snowflake support. Snowflake customers will be able to use EZOPS’ AI models to analyze data stream patterns for anomalies, and then escalate said anomalies within EZOPS Workflow for further triage and analysis.

Trifacta Delivers Head Start on Cloud Data Engineering With New Template Gallery

On July 27, Trifacta debuted pre-built cloud data engineering templates to further enable what they’re calling “self-service data management.” The templates will allow Trifacta users to tweak pre-configured data engineering workflows to suit their needs, then quickly deploy them. Some examples of the available templates include transforming data to a target schema using a mapping table, identifying sentiment keywords and calculating NPS, and importing data from Google Cloud Storage to BigQuery.


Kyndryl Names David Wyshner As Chief Financial Officer

Kyndryl, the new separate company of IBM’s Managed Infrastructure Services, has appointed David Wyshner as the company’s CFO. Wyshner was most recently the CFO of XPO Logistics; prior to that, Wyshner led the separation of Wyndham Worldwide into three separate companies during his time as CFO there.

Informatica Appoints Elizabeth Rafael to Board of Directors

On July 26, Informatica announced that Betsy Rafael has joined the Informatica board of directors, as well as the chair of the audit committee. Most recently, Rafael was the Chief Transformation Officer at GoDaddy. Preceding her stint at GoDaddy, Rafael served as Vice President and Corporate Controller and Principal Accounting Executive at Apple, and Vice President, Corporate Finance at Cisco.