Year: 2022

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August 5: From BI to AI (Alteryx, Databricks, dbt labs, Hazelcast, MicroStrategy, Snowflake, Zilliz)

Financials

Alteryx Announces Second Quarter 2022 Financial Results
Alteryx announced its Q2 2022 financial results on August 2. Revenues of $180.6M were up 50% year over year; specifically, subscription revenue doubled to nearly $81M. AYX saw a significant boost in the market based on the revenue growth spurt, though they ended the quarter with a net loss of $106.7M.

MicroStrategy Announces Q2 2022 Financial Results, Separates Chairman and CEO Roles

BI and analytics company MicroStrategy announced their Q2 2022 financial results this week as well. The $122.1M in revenues for this quarter were slightly lower than the same quarter last year, though subscription services revenues were up 5% year over year at $34.1M. As of the end of the quarter, June 30, MicroStrategy had $918M in operational loss due to their Bitcoin holdings tumbling in value, though some of that value has since been recovered.

MicroStrategy also revealed that they would be dividing their Chairman and CEO roles. On August 8, current CEO and Chairman of the Board Michael Saylor will step into the new role of Executive Chairman, while retaining his Chairman of the Board role. Saylor will focus on innovation and long-term corporate strategy, while heading the Board’s Investments Committee and supervising MicroStrategy’s bitcoin acquisition strategy. Current President Phong Le will become the new CEO, in charge of MicroStrategy’s corporate strategy execution, and serve on the Board of Directors as well.

Snowflake to Announce Q2 2023 Financial Results
Snowflake announced that it will release its financial results for Q2 2023 on Wednesday, August 24, following the close of the US markets that day. Snowflake will hold a conference call at that time to discuss the results.

Launches and Updates

Databricks Makes Photon Engine Generally Available

This week, Databricks announced that its lakehouse query engine, Photon, was now generally available across all of the major cloud platforms. New features with the GA release include speed upgrades across numerous functions: vectorized sort (3-20x performance gain over Apache Spark), accelerated window functions performing calculations across table rows that are 2-3x faster than before; and stateless Structured Streaming workloads at 20% of the cost of running similar workloads on traditional Spark. Though Photon’s initial focus on SQL was to enable data warehouse workloads on data lakes, language coverage has been expanded to include modern DataFrame and SparkSQL workloads.

dbt Labs Debuts Technology Partner Program

dbt Labs formally launched its dbt Labs Technology Partner Program this week. Over 50 partners are participating, from categories such as data quality and business intelligence, including Airbyte, Monte Carlo, and ThoughtSpot. Partners integrate their software to extend dbt’s capabilities, while gaining an increased connection to dbt’s userbase.

Hazelcast Launches Viridian Serverless

Realtime data platform Hazelcast released the beta version of Hazelcast Viridian Serverless, a process that grows and shrinks a cluster based on the current workload. Not having to plan for specific sizing up front can speed up app development, and it simplifies the provisioning process. Viridian Serverless is currently available on AWS, with GCP access in the works.

Zilliz Announces Key Contributions to Milvus 2.1

Vector database company Zilliz, creators of the Milvus open source vector database, announced significant contributions to the recent Milvus 2.1 release. These contributions include performance boosts throughout, improvements to scalar data processing to support hybrid search, and tutorials to help users build apps on top of Milvus.

Hiring

Alteryx Appoints Doniel Sutton as Chief People Officer | Alteryx
On August 4, Alteryx announced that it had appointed Doniel Sutton as their Chief People Officer. Sutton brings over 20 years of human resources and strategic experience to Alteryx. She was previously the Chief People Officer at Fastly, and has held senior HR leadership roles at Paypal, Prudential, Bank of America, and Honeywell.

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Calero-MDSL Acquires Network Control to Support Mid-Market TEM Demand

On August 2, 2022, Calero-MDSL announced the acquisition of Network Control, a telecom expense and managed mobility services vendor based in Waverly, Iowa. This acquisition continues the acquisitive streak of Calero-MDSL and increases its status as the largest telecom expense management solution in terms of spend under management.

Network Control provides telecom expense management and managed mobility services. Founded in 1998 and headquartered in Waverly, Iowa, Network Control was privately held with no outside investment. Network Control is owned by Mark Hearn, a long-time TEM executive who purchased the company in 2011. Amalgam Insights estimates that Network Control has roughly doubled in headcount to approximately 100 employees between the 2011 acquisition and the 2022 purchase by Calero-MDSL.

With this acquisition, Calero-MDSL is making greater strides into the mid-market in acquiring a client base that collectively includes over 200,000 devices and $300 million in spend under management over 75 customers. From a pure spend perspective, Network Control does not represent a substantive addition to Calero-MDSL’s estimated $22 billion under management as the largest TEM in terms of spend under management. However, Network Control brings several important skills to Calero-MDSL that will be vital for the continued growth of the combined company.

First, Network Control has shown the ability to consistently win new business in the mid-market enterprise and is known for its retention. In Amalgam Insights’ CIO Guide for Wireless Expense Management, Network Control was listed as one of Amalgam Insights’ Distinguished Vendors based on its 98%+ retention rate for customers, with the majority of account losses over time coming from merger and acquisition activity or from the cessation of business activities. Mid-market enterprises between $1 million and $20 million in annual telecom spend is an increasingly competitive space for the large TEM vendors that are reaching the practical limits of saturation among the Global 2000 where they have traditionally focused. As TEM has become an established business practice over the past 15-20 years, TEM vendors have been able to polish both their software platforms and managed services capabilities and now are better positioned to provide these capabilities downmarket to support the next $200 billion in global mid-market telecom and technology spend that has traditionally been almost a greenfield market.

In addition, Network Control brings strong managed services capabilities for managed mobility, with approximately 100 employees trained in supporting a managed mobility services organization across operations, logistics, sales, and other business functions which will be valuable to Calero-MDSL in bolstering existing managed mobility capabilities. Network Control is known for its flexibility and client-centric focus in bringing new services to clients as well as for the quality of customer service provided.

Network Control also has a sustained record of winning deals against the likes of Tangoe and Sakon, which happen to be two of Calero-MDSL’s largest rivals in the TEM space. In our CIO Guide, we saw that Network Control ran into competitive deals in approximately 80% of their sales, which was indicative both of the relatively educated nature of potential customers and Network Control’s ability to win against larger vendors.

What to Expect?

First, for mid-market businesses between $100 million and $5 billion in annual revenue, expect increased attention from TEM companies seeking your business to manage your telecom spend. They are seeking environments that have been manually managed or managed with spreadsheets and fall under the IT Rule of 30, which states that any unmanaged IT spend category averages 30% in duplication and waste. This will also be a shift for TEM and MMS vendors that have traditionally sold into the mid-market and found that their biggest competition was against the status quo. As this market starts to shift towards what is being called the “mid-market” or the “mid-enterprise,” expect to see more competitive deals. Calero-MDSL has acquired a company that has a history of winning mid-market business against Calero-MDSL’s biggest rivals based on understanding mid-market pain points and service needs. By adding marketing and sales muscle to Network Control’s operational capabilities, Calero-MDSL has an opportunity to support the mid-market in an unprecedented way.

Second, this acquisition looks like it could kick off a second wave of TEM consolidation. In the early 2010s, there was a massive wave of consolidation in the TEM market driven by venture capital-backed vendors seeking exits or running out of funding. In the 2020s, the situation is slightly different as the firms that have remained to this day tend to be privately owned and profitable companies that have established both best practices and processes to support loyal customer bases. We have started to see the acquisition of these private firms with the acquisitions of Vision Wireless and Wireless Analytics by Motus and with this acquisition, but there are at least a half dozen additional firms with strong mid-market experience that would be strong candidates for a similar acquisition or rollup. However, the big caveat here is that any acquisition of these companies needs to be coupled with a strong customer service culture as the mid-market TEMs Amalgam Insights covers frequently average 98% retention or higher with over 100% wallet share; this is a demanding market where technology, services, and client management must be aligned.

Third, this acquisition shows that the cost of acquiring talent is still significant in the TEM world. Calero-MDSL would have needed an extra year to find the volume of high-level talent that they are getting at one time with the acquisition of Network Control. The ability to find personnel with experience in managing the spend and procurement of millions of dollars in annual technology spend is still relatively rare. This skill will become increasingly necessary in the recessionary times that we are currently facing. Companies cannot simply eliminate technology, so they will need to financially reconcile their environments both with in-house and third-party resources. Network Control has proven its ability to maintain a high level of service by maintaining a high staff-to-client ratio, a practice that Amalgam Insights recommends keeping as the relative cost of labor is smaller than the cost of finding a new customer.

Fourth, it is safe to assume that Network Control was purchased for its talent, capabilities, and client base rather than its software platform. Although Network Control’s TEMNet is a functional platform, the amount of investment that Calero-MDSL has put into its platform ensures that customers will eventually be migrated to this platform. As long as this migration is handled carefully, this should not be a challenge. Calero-MDSL has prior experience in migrating clients from previous acquisitions A&B Groep and Comview, among others.

Overall, Amalgam Insights believes that this acquisition will be accretive to Calero-MDSL both in providing greater capacity to support managed mobility services and to learn the demands of mid-market clients from an experienced team. This acquisition also will eventually provide Network Control clients with access to the Calero-MDSL platform, which has been built to support global environments and now also includes Unified Communications as a Service and Software as a Services support. Amalgam Insights believes this acquisition demonstrates Calero-MDSL’s continued commitment to expanding its market share and providing telecom and technology expense savings to a wider clientele of organizations.

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July 29: From BI to AI (Datafold, Domino Data Lab, Expert.ai, FeatureByte, Fiddler, Hightouch, Informatica, Microsoft)

Funding and Finance

FeatureByte Emerges from Stealth with $5.7M Seed Round

Feature engineering and management platform FeatureByte launched this week, announcing a $5.7M seed round led by Glasswing Ventures and Tola Capital. The funding will go towards scaling up R+D and go-to-market operations. The FeatureByte founders came from DataRobot, where CEO Razi Raziuddin was the SVP of AI Services and Chief Product Officer Xavier Conort was the Chief Data Scientist. FeatureByte looks to simplify the creation and management of AI model features.

Informatica Reports Q2 2022 Financial Results

On July 27, Informatica announced its Q2 2022 financial results. Revenues of $372M beat expectations by $7.8M; earnings were above expectations at $0.16 per share. INFA is up since the earnings announcement.

Microsoft Announces Q4 2022 Financial Results
On July 26, Microsoft announced its Q4 2022 financial results. Revenues ($51.87B) and earnings ($2.23/share) were both slightly lower than expected. MSFT dipped a bit in the market, but ended the week up.

Updates and Launches

Expert.ai Adds New Features to its Natural Language Platform

Natural language platform Expert.ai made improvements to its natural language platform. Key new features include improved data labeling with active learning capabilities, automatic generation of extraction rules enabling users to generate rule-based models, and pre-trained knowledge models in specific domains.

Fiddler Updates Machine Learning Model Management

Fiddler, a model performance management platform, revealed new capabilities this week. Fiddler customers will now be able to use vector monitoring to better observe models in production involving unstructured data, such as ones based on natural language processing and computer vision. Fiddler will also surface more low-frequency events that can contribute to subtle model drift while concealing issues such as fraudulent transactions. Finally, Fiddler has also unveiled a “single pane of glass” user interface, allowing data science and MLOps teams to view and manage models from a centralized dashboard.

Partnerships

Datafold and Hightouch Debut Integration
Data reliability company Datafold and data activation platform Hightouch announced an integration to alert data engineers whenever a dbt data model change will impact data involved in a Hightouch sync. Hightouch automates data integration from data warehouses to business systems such as CRMs, ERPs, and custom applications; data model changes upstream or downstream can break data syncs. Datafold’s Data Diff combines with Hightouch to alert data engineers to potential issues before they become issues in production.

Domino Data Lab and Alexander Thamm Partner to Scale Data Science in Germany, Austria, Switzerland
Domino Data Lab announced a partnership with consultancy Alexander Thamm to help customers in the German-speaking DACH region accelerate their data science implementation timelines. The Data Science Journey Accelerator will pair Domino’s Enterprise MLOps platform with Alexander Thamm’s consulting services for data science and data engineering. Offerings will include assessments in data strategy, the data science lifecycle, and business value, as well as creating proofs of concept.

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July 22: From BI to AI (Askdata, Cloudera, DataRobot, Datatron, Microsoft Azure, Oracle, Pecan AI, SAP, Talend)

Hiring

Debanjan Saha Steps Into DataRobot Interim CEO Role

DataRobot President and COO Debanjan Saha has been appointed interim CEO in the wake of Dan Wright stepping down from the CEO position. Saha joined DataRobot in February 2022. Prior to DataRobot, Saja was the VP and GM of Data Analytics at Google, as well asthe VP and GM for Amazon Aurora and RDS. Saha also spent a decade at IBM, primarily in storage and analytics.

Wright will continue with DataRobot in an advisory role during the executive search for a permanent CEO.

Launches and Updates

Datatron Releases Version 3.0

MLOps platform Datatron released version 3.0 this week. Key new features include integration with JupyterHub, allowing data scientists to operationalize models directly from their notebook-interface coding environment; simpler deployment and management facilities ffor all three major cloud platforms without needing to learn or manage Kubernetes; and an updated logging and operations dashboard, along with single sign-on support.

Oracle and Microsoft Present Oracle Database Service for Microsoft Azure

On July 20, Oracle and Microsoft announced Oracle Database Service for Microsoft Azure. Azure customers will be able to provision, access, and monitor Oracle Database services in Oracle Cloud Infrastructure, connecting OD services running on OCI with apps in Azure that use data from those services. Oracle Database Service for Microsoft Azure is generally available now.

Pecan AI Debuts One-Click Data Science Model Deployment

Low-code automated predictive analytics company Pecan AI added one-click machine learning model deployment to its platform this week. Pecan also added model monitoring targeted towards low-code users, alerting them when models show signs of degradation. These two additions join existing features on the Pecan platform to automate all aspects of model creation and deployment.

Partnerships

Talend Enhances Cloudera Data Platform Support

Data integration platform Talend added new certifications for Cloudera Data Platform on the Public Cloud, and CDP data services including Data Engineering and Data Hub. Talend also revealed new native integrations with CDP Engineering, allowing data teams to autoscale Spark jobs without needing to manually configure and scale clusters.

Acquisitions

SAP Acquires Search Analytics Startup Askdata

SAP has acquired Italian search-driven analytics startup Askdata for an undisclosed sum. Askdata uses machine learning and natural language processing models to make it easier for less-technical users to interrogate data in place. Askdata will become part of a future analytics solution for SAP Analytics Cloud.

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July 15: From BI to AI (Alteryx, AssemblyAI, AWS, Deci, Microsoft, SAP, SingleStore, Tecton, TIBCO)

Funding and Financials

In addition to the funding rounds mentioned below, Alteryx, Microsoft, and SAP all announced the release dates for their next quarterly earnings reports. Alteryx will report their Q2 financial results on Tuesday, August 2; Microsoft will report their Q4 financials on Tuesday, July 26; and SAP will report their Q2 financials on Thursday, July 21.

AssemblyAI: $30M Series B Round

Automatic speech recognition platform AssemblyAI picked up $30M in Series B funding. Insight Partners led the round, with participation from existing investors Accel and Y Combinator. AssemblyAI will use the funding to grow their AI research team and accelerate product development.

Deci Raises $25M Series B

Deep learning AI building company Deci raised a $25M Series B round. Insight Partners led this round as well (busy week), with participation from existing investors Emerge, Fort Ross Ventures, Jibe Ventures, and Square Peg, and new investor ICON. Deci will use the funding to grow go-to-market efforts and R+D.

SingleStore Announces $116M F Round, New CFO and GC

Cloud-native analytics database provider SingleStore announced a $116M Series F round of financing this week. Goldman Sachs Asset Management led this round, with participation from current investors Dell Technologies Capital, GV, Hewlett Packard Enterprise, IBM Ventures, and Insight Partners, as well as new investor Sanabil Investments.

SingleStore also welcomed two new [executive level] hires in recent weeks. Chief Financial Officer Brad Kinnish joins SingleStore from Aryaka Networks, where he also served as CFO. Prior to Aryaka, Kinnish was also the CFO at Marin Software, and the managing director of Software Investment Banking at Deutsche Bank. New General Counsel Meaghan Nelson was previously the associate general counsel at Veeva Systems as part of over a decade of legal experience.

Tecton Raises $100M Series C Round

Machine learning feature platform Tecton raised a $100M Series C funding round. New investor Kleiner Perkins led the round, with participation from existing investors Andreessen Horowitz and Sequoia Capital, along with new investors Bain Capital Ventures, Databricks Ventures, Snowflake Ventures, and Tiger Global. The funding will go towards additional hiring in engineering and go-to-market teams.

Updates and Launches

AWS Makes Three New Serverless Analytics Offerings Generally Available

AWS announced the general availability of three new serverless analytics offerings; with these, customers will be able to analyze massive amounts of data without needing to manage the supporting infrastructure. Amazon EMR Serverless will allow customers to run analytics apps using Apache Spark and Hive. Amazon MSK Serverless will simplify realtime data ingestion and streaming. Finally, Amazon Redshift Serverless will allow customers to manage high-performance data warehousing and analytics workloads without having to micromanage clusters.

TIBCO Unlocks the Power of Master Data Management Software-as-a-Service with the New TIBCO Cloud EBX | TIBCO Software
TIBCO ModelOps Significantly Improves Efficiency and Flexibility Across the Enterprise with Impactful AI | TIBCO Software

TIBCO revealed two major releases this week. TIBCO Cloud EBX is a SaaS-based Master Data Management solution, will let users manage their corporate data from anywhere. EBX is part of TIBCO Cloud Passport, a new consumption-based pricing plan enabling SaaS for various TIBCO capabilities. Key features of TIBCO Cloud EBX include a model-driven process for data management; the ability to manage every data domain with hierarchy management, match-and-merge functionality, and search and query capabilities; and easy ways to import and export data in bulk and access it via APIs.

TIBCO ModelOpswill provide self-service data science access to teams including business users, with the aim of deploying more machine learning models faster. All common model formats are supported in ModelOps, and governed models can currently be added to TIBCO Spotfire, TIBCO Data Virtualization, and TIBCO Streaming, with more options to follow.

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July 8: From BI to AI (Databand.ai, IBM, Meta, Ontotext)

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

Acquisitions

IBM Expands Observability Capabilities with Databand.ai Acquisition

IBM announced Wednesday that they had acquired Databand.ai, a data observability software provider. Databand.ai looks for issues such as data anomalies, missing or incomplete data, and other problems that come up during the data transformation process. IBM suggests that pairing Databand.ai with IBM Observability by Instana APM and Watson Studio will combine application performance monitoring and data observability into a more complete observability platform spanning a broader spectrum of IT ops. Databand.ai employees will join IBM’s Data and AI group.

Launches and Updates

Meta Debuts Improved Language Translation Model and Dataset

Meta announced Wednesday that their AI researchers had built an AI model, NLLB-200 (No Language Left Behind) that significantly improves the accuracy of machine translation between 200 different languages. Meta also compiled the FLORES-200 dataset to measure NLLB-200’s language performance to ensure high-quality translations. Developers will be able to access both NLLB-200 and FLORES-200, and Meta will award $200,000 in grants for “impactful uses” of NLLB-200; specifically, researchers working in linguistics, machine translation, and language technology, as well as nonprofits translating two or more African languages, are invited to apply.

Ontotext Releases GraphDB 10.0

Ontotext announced GraphDB 10.0, the latest major release of their database engine. Key new features include a new high-availability cluster architecture with higher uptime, zero data loss, better fault tolerance, and better recovery from failures; an improved graph path search algorithm that can run in parallel mode in multicore environments, enabling faster processing on complex searches and the ability to handle more concurrent requests; improved full text search; and a simplified upgrade path requiring no development effort to upgrade from free to standard to enterprise editions of GraphDB.

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July 1: From BI to AI (Databricks, Dataiku, Immuta, Kyligence, Matillion, Opaque Systems, Sigma Computing, Snowplow, TigerGraph, Timecho)

Databricks Data + AI Announcements

Databricks Debuts Improvements to Data Lakehouse at Data + AI Summit

At Databricks’ Data + AI summit this week, Databricks announced myriad improvements to their Databricks Lakehouse Platform. Key enhancements include improvements to data governance and the Unity Catalog, public (Marketplace) and secure (Cleanroom) data asset sharing, MLflow 2.0 with simplified machine learning model deployment, and resource autoscaling for performance and cost efficiency in Delta Live Tables. Databricks also significantly augmented their data warehousing capabilities with an assortment of developer-focused improvements. But the announcement previewing Photon, their “record-setting query engine for lakehouses,” noting performance up to 12x better than traditional cloud data warehouses, marked a significant shot across Snowflake’s bow.

Notably, Databricks also open-sourced its Delta Lake contributions, to drive Delta Lake adoption and compete with Apache Iceberg and Apache Hudi.

Several companies made related announcements this week about their partnerships with Databricks in concert with the summit. Data security platform Immuta integrated its policy enforcement engine into Databricks’ Unity Catalog for better enforcement of data access policies. Matillion made Matillion ETL available on Databricks Partner Connect, permitting joint customers to more easily import business data into their Databricks lakehouse without requiring pre-configuration. Sigma Computing announced their new Databricks partnership and integration, providing a no-code spreadsheet interface into the lakehouse. And behavioral data creation platform Snowplow also announced a partnership with Databricks. Joint customers will be able to integrate Snowplow data into their Databricks lakehouse, along with Snowplow’s new custom-built web models, to build data-driven apps and composable customer data platforms (CCDPs).

Amalgam Insights’ Hyoun Park attended the Data + AI summit, and his perspective will be published next week.

Other Launches and Updates

Kyligence Debuts Unified Metrics Store

OLAP platform Kyligence announced Kyligence Zen, a unified metrics store platform. Kyligence Zen automates data pipelines between data lakes and warehouses and the Kyligence OLAP database, providing a centralized location for data analysts for accessing and combining data metrics.

TigerGraph Updates TigerGraph Cloud

Graph analytics platform TigerGraph added new features to its graph database as a service TigerGraph Cloud. The improvements are primarily enterprise-focused: enterprise identity and access management, connectivity meeting enterprise-level security standards, and broader accessibility with more options for regional access on all three major cloud providers, as well as expanding the free-tier support for developer learning to Azure.

Funding

Opaque Systems Raises $22 Million in Series A Funding

“Confidential computing” secure data analytics platform Opaque Systems has raised $22M in Series A funding. Walden Catalyst Ventures led the round, with participation by existing investors FactoryHQ, the House Fund, Intel Capital, and Race Capital, as well as new investors Storm Ventures and Thomvest Ventures. The funding will go towards hiring and accelerating R+D.

Snowplow Raises $40M in Series B Funding

In addition to the Databricks partnership mentioned earlier, Snowplow raised $40M in Series B funds this week. NEA led the funding round, with participation from existing investors Atlantic Bridge and MMC. Snowplow plans to use the funds for hiring, scaling globally, and broadening support for more data types on its platform.

Timecho Raises $10M Seed Round

IoT-native time-series database Timecho, based on open source Apache IoTDB, raised $10M. Sequoia China led the round, with additional support from Cloudwise, Gobi China, and Koalafund. The funding will go towards R+D to better support enterprise-scale IoT needs such as better end-edge cloud collaboration.

Hiring

Bridget Shea Appointed as Dataiku’s New Chief Customer Officer

Dataiku has appointed Bridget Shea as its new Chief Customer Officer. Shea has served in an advisory role with the Dataiku leadership team for several years. Prior to joining Dataiku, Shea was the Chief Customer Officer at Mural, a collaborative intelligence company, as well as leading other global go-to-market teams at Datorama, TellApart, and Yext.

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June 24: From BI to AI (Anaconda, Ataccama, Databricks, Dataiku, DataRobot, Domino Data Lab, Precisely, Prophecy, PythonAnywhere, Starburst, Varada)

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

Funding

Bain Capital Invests $150M into Data Management Platform Ataccama

On June 22, data management platform provider Ataccama announced that they had received $150M in growth capital from Bain Capital Tech Opportunities as a minority investment. The funds will go towards sales and marketing, R+D around new product innovation, and global expansion. Ataccama has only taken funding once before in the form of a $500K seed round in 2010 when it spun off from big data company Adastra; this much more significant investment indicates a desire to grow more quickly to take on the IPaaS competition like Informatica and Talend.

Launches and Updates

At Everyday AI, Dataiku Debuts Dataiku 11

At their Everyday AI conference this week in London, data science and AI platform Dataiku launched Dataiku 11. Key features of this major release include optimized tooling for advanced users, an integrated data labeling framework for inline image annotation, a visual interface for computer vision tasks allowing data scientists at all levels to work on models for complex object detection and image classification, and expanded capabilities around Responsible AI and AI governance. Dataiku 11 also includes tools for non-coding team members such as a no-code visual time series forecasting capability, a centralized feature store and workflows for more easily sharing and reusing existing work, and “what-if” accelerators to evaluate potential business outcomes in a codeless way.

Domino Data Lab Announces Nexus, a Hybrid MLOps Architecture

First previewed at the Rev 3 conference last month, Domino officially launched its Nexus hybrid MLOps architecture this week. Customers using Nexus will be able to use owned on-prem NVIDIA GPUs for cost optimization, while also having the ability to scale workloads to include cloud-based GPUs when they don’t have enough capacity on-prem. NVIDIA is a launch partner of NEXUS, and Domino has joined the NVIDIA AI Accelerated program as part of their ongoing partnership around building, managing, and deploying GPU-trained models.

Precisely Launches Data Integrity Suite

Data integrity platform Precisely announced the Precisely Data Integrity Suite, a collection of SaaS modules that can be deployed individually or in concert to provide businesses with trustable data. The Data Integration, Data Observability, and Data Governance modules are now available for early access, while modules for Data Quality, Geo Addressing, Spacial Analytics, and Data Enrichment are forthcoming.

Prophecy Launches Low-Code “Prophecy for Databricks”

Low-code data engineering platform Prophecy launched Prophecy for Databricks this week. Prophecy for Databricks is a drag-and-drop interface to create and launch data pipelines on Spark, empowering data analysts to become “citizen data engineers.” The visual interface generates PySpark or Scala code to create these pipelines, then uses standard Databricks Workflows to manage the pipelines in production. Databricks users can access Prophecy for Databricks through Databricks Partner Connect.

Acquisitions

Anaconda Acquires Cloud-Based Development Environment PythonAnywhere

Earlier this week, Anaconda acquired cloud-based Python development and hosting platform PythonAnywhere. Anaconda users will now be able to use Python in a cloud environment, accessing the PythonAnywhere development environment from any web browser and allowing for better team collaboration and asset sharing.

Starburst Acquires Data Lake Analytics Accelerator Varada

Analytics company Starburst announced this week that they had acquired Varada, a data lake analytics accelerator. Varada’s proprietary indexing technology drew Starburst’s interest in hopes of advancing the performance and cost efficiency of their existing query engine. The rollout is expected to be quick; Starburst is expecting to roll Varada’s capabilities out to select customers by the end of July, with general availability in the fall of 2022.

Hiring

Chris Riley Joins DataRobot as President of Worldwide Field Operations

On June 21, DataRobot announced that they had appointed Chris Riley as the President of Worldwide Field Operations. Riley comes to DataRobot from Automation Anywhere, a robotic process automation company, where he served as the Chief Revenue Officer. Prior to that, Riley spent time at Dell as the President of Dell Technologies Select, and as President of the Americas for Dell Technologies.

Events

Databricks Data + AI Summit 2022, June 27-30

The 2022 Databricks Data + AI Summit will be held in-person in San Francisco and virtually, June 27-30, with the theme “Destination Lakehouse” to focus on how the modern data stack functions to turn data into actions more quickly. Key speakers include Databricks co-founders Ali Ghodsi, Matei Zaharia, and Reynold Xin; Google Brain and Coursera co-founder Andrew Ng; Christopher Manning, director of the Stanford AI Lab; Insitro founder and CEO Daphne Koller; Hidden Door co-founder and CEO Hilary Mason; AI pioneer Peter Norvig; Girls Who Code CEO Tarika Barrett; and Thoughtworks director Zhamak Dehghani. The conference is sold out in person, but to attend virtually, register at Data + AI Summit.

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June 17: From BI to AI (Anaconda, Domino Data Lab, H2O.ai, Informatica, KNIME, Matillion, Okera, Snowflake, Yellowbrick)

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

Snowflakes in June

The biggest news: Snowflake Summit 2022 was this week, and a wide variety of data companies released announcements in conjunction with the conference, whether technical or fiscal in nature.

Snowflake Releases Unistore, A Workload Combining Transactional and Analytical Data in One Platform

Snowflake itself had several major announcements at Snowflake Summit 2022. The first covered the debut of Unistore, a workload that will allow Snowflake users to store transactional and analytical data together in a Snowflake data warehouse. Snowflake’s new Hybrid Tables will enable this new approach; customers will be able to perform fast analytics on transactional data stored in Snowflake for more timely understanding, and build transactional apps atop Snowflake.

Snowflake Introduces Native Application Framework

Snowflake also announced a Native Application Framework. Developers will be able to build data applications on Snowflake and monetize them on the Snowflake Marketplace, allowing Snowflake consumers to install and run those applications securely in their own Snowflake instances without needing to move or share data. In conjunction with this, Informatica launched their new enterprise data integrator on Snowflake, reflecting an expanded partnership with Snowflake.

The Register interviewed Amalgam Insights’ Hyoun Park on Snowflake’s Announcements, covering Unistore and the Snowflake Native Application Framework.

Snowflake Expands Native Python Support and Data Access with Snowpark for Python

Finally, Snowflake announced a number of changes demonstrating stronger Python support for machine learning and application development on Snowflake. First, Snowflake launched Snowpark for Python into public preview, broadening from existing Scala and Java support. This means that Python’s open-source packages and libraries are now accessible within Snowpark, providing a strong foundation for the most popular language for building machine learning models. Additional support for Python developers includes a new Streamlit integration for easier app development on Snowflake; Snowflake Worksheets for Python to enable development of machine learning models, pipelines, and applications directly in Snowsight; large memory warehouses to support memory-intensive operations like feature engineering and model training on large datasets, enabled through Snowflake’s Anaconda integration; and SQL Machine Learning, allowing data analysts to more easily use machine learning algorithms without requiring advanced knowledge. The first algorithm available is time-series forecasting. Finally, Snowflake also increased data access with better support for ingesting and transforming streaming data, and working with data external to the Snowflake Data Cloud, even on-prem data, while still conferring some of the advantages of storing data in Snowflake.

Funding

Domino Data Lab Reveals Investment from Snowflake Ventures

Domino Data Lab announced an investment from Snowflake Ventures this week for an undisclosed amount, following up on Snowflake Ventures’ previously unannounced participation in Domino’s Series F funding round last October. The additional investment demonstrates the strength of the Snowflake-Domino partnership being robust enough for Snowflake to take an equity stake in Domino, rather than being solely a technical partnership.

Matillion Announces Snowflake Ventures Investment

Data integration platform Matillion also announced an investment from Snowflake Ventures. As part of this ongoing “investipartnership,” Matillion will be among the first Snowflake data integration partners to use the just-announced Snowflake Native Application Framework by making Matillion connectors available directly within Snowflake.

Launches and Updates

KNIME Software Release: Improved Python, Snowflake Integrations

KNIME announced the latest release of their data science platform. Key new features include upgrades to KNIME’s Python support with a built-in Python environment and the ability to write KNIME extensions entirely in Python, as well as a Snowflake integration that allows users to build machine learning models in H2O.ai, and then push the model down to Snowflake for predictions.

Okera Now Generally Available on Snowflake

Data security and governance company Okera announced that Okera was now available on Snowflake as a SaaS offering for Snowflake Data Cloud. Okera’s universal data authorizaton policies are automatically translated into Snowflake data access governance controls, allowing native data security policy enforcement within Snowflake.

Yellowbrick Launches Latest Version of its Data Warehouse

Cloud data warehouse Yellowbrick released a new version of its platform this week. Key features include on-prem and AWS deployment options (Azure and Google Cloud Platform coming in Q3), data lake integration using Parquet, separation of compute and storage for more elastic scaling on demand, and multiple payment models (consumable either on-demand or through a subscription based on fixed capacity). Yellowbrick also announced two new partnerships with Saarthee and Saxon, two data and analytics companies.

Partnerships

H2O.ai Expands Snowflake Partnership

H2O.ai continues to grow its Snowflake partnership. Users are able to use H2O.ai machine learning capabilities on the data within their Snowflake environment; H2O.ai is expanding support for financial services, manufacturing, and healthcare customers doing machine learning.

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Market Alert: Vendr Raises $150 Million B Round to Help Enterprises Purchase SaaS More Efficiently

On June 16, 2022, Vendr, a SaaS (Software-as-a-Service purchasing platform) announced a $150 million Series B round co-led by prior investor Craft Ventures and novel investor SoftBank Vision Fund 2 and joined by Sozo Ventures, F-Prime Capital, Sound Ventures, Tiger Global, and Y Combinator. The company states that this funding will drive platform enhancements.

Why this funding announcement matters

To fully contextualize this announcement, Amalgam Insights will dig into the context of the macroeconomic issues driving the importance of this announcement, the tactical importance of a SaaS purchasing solution in the Technology Lifecycle Management (TLM), and the nature of the investment compared to other historical funding announcements in the TLM space.

Macro Trends for Corporate Spend Reduction

First, this announcement comes at a time when the United States is facing inflation that approaches double-digits. The current 8.6% inflation rate in this country threatens to devour the average 8.19% net margin that publicly traded companies (excluding financial services) currently achieve. In addition, we are facing a global recessionary trend driven by COVID, supply chain issues, geopolitical strife including the occupation of Ukraine, strained Sino-US relations, inconsistent oil and gas policies, and an excess of money supply created over the past several years. In the face of these global challenges, it is prudent for companies to seek to reduce discretionary costs where it is possible and to shift those costs to strategic growth areas. Traditionally, recessions have been a time when strong companies invest in their core so that they can execute when the economy picks up again.

SaaS as a Strategic and Expanding Complex Spend Category

In this context, SaaS is a massive, but complex, opportunity to cut costs. Amalgam Insights estimates that the SaaS market has grown 25% per year in each of the last two years. Multiple studies show that enterprises that have reached the billion-dollar annual revenue threshold average over 300 apps directly purchased by the organization and over 900 apps running over their networks, either on in-office networks or on employee devices. The hundreds of apps here obviously equate to hundreds, possibly thousands, of accounts and bills that can be consolidated, negotiated, and potentially rationalized to concentrate spend on strategic vendors and gain purchasing power. It is not uncommon to find large enterprises using 20 or more different project management solutions, just to look at one SaaS subcategory.

This rationalization is vital if enterprises are to take the IT Rule of 30 seriously. Amalgam Insights states that the IT Rule of 30 is that any unmanaged IT category averages a 30% opportunity to cut costs. But that 30% requires following the Technology Lifecycle to fully uncover opportunities to cut costs.

Technology Lifecycle Management

The majority of companies that Amalgam Insights speaks to in the IT expense role limit their diligence in IT spend to the right side of this lifecycle including timely bill payment, possibly cross-charging to relevant business entities and cost centers, and right-sizing expenses by finding duplicate or over-provisioned accounts. While this is necessary to execute on the IT Rule of 30, it is not sufficient. In the SaaS space, Amalgam Insights believes there is conservatively a $24 billion spend reduction opportunity globally based on improved SaaS purchasing and negotiations. At the micro level, this equates to a 2 million dollars for the average billion-dollar+ enterprise, with results varying widely based on SaaS adoption (as SaaS only makes up 30% of overall enterprise software spend globally), company size, and level of internal software contract knowledge.

Putting The Investment in Perspective

Amalgam Insights understands the scale of this business opportunity. Even so, this $150 million B round represents a massive round in the Technology Lifecycle Management space. Consider other large funding rounds in this space including:

Zylo’s 2019 $22.5 million B Round for SaaS Management

BetterCloud’s 2020 $75 million F Round for SaaS Management

Productiv’s 2021 $45 million C Round for SaaS Management

Beamy’s 2022 $9 million A Round for European SaaS Management

Torii’s 2022 $50 million B Round for SaaS Management

and looking further across the Technology Management spectrum

Cloudability’s 2016 $24 million B Round for IaaS Management (later acquired by Apptio)

CloudCheckr’s 2017 $50 million A Round for IaaS Management (later acquired by NetApp)

CloudHealth’s 2017 $46 million D Round for IaaS Management (later acquired by VMware)

MOBI’s 2015 $35 million investment round for Managed Mobility (later acquired by Tangoe)

I hasten to add here that more is not always better. But this range of funding rounds is meant to show the amount of investment that typically goes into solutions designed to manage technology expenses, inventory, and sourcing. At first glance, Vendr’s funding round may seem like just another funding announcement in the billions and trillions of dollars involved in the tech sector to those who do not cover this space closely. But as someone who has covered telecom, cloud, and SaaS expense management closely for the last 14 years, this round stands out as a massive investment in this space.

In addition, the investors involved in this round are top-tier including Craft Ventures, where founder and ex-Paypal founder David Sacks has been a proponent of Vendr, and the combination of Tiger Global and Softbank, which may be the two most aggressive funds on the planet in terms of placing big bets on the future. The quality of both smart money and aggressive money in this investment during a quasi-recessionary period speaks to the opportunity that exists here.

What to expect from this round?

The official word from Vendr so far is that this funding round is about data and platform. Vendr acquired SaaS cost and usage monitoring firm Blissfully in February 2022 to bring sourcing and expense management together and support the full lifecycle for SaaS. Amalgam Insights expects that some of these funds will be spent to better integrate Blissfully into Vendr’s operations. In addition, the contract information that Vendr has represents a massive data and analytics opportunity, but this will likely require some investment into non-standard document management, database, machine learning, and data science technologies to integrate documents, tactics, terms, and results. Whether this investment takes the form of a multi-modal database, graph database, sentiment analysis, custom modeling, process mining, process automation, or other technologies is yet to be seen, but the opportunity to gain visibility to the full SaaS lifecycle and optimize agreements continuously is massive not only from a cost perspective, but also a digital transformation perspective. The data, alone, represents an immediate opportunity to either productize the benchmarks or to provide guidance to clients with ongoing opportunities to align SaaS usage and acquisition trends with other key operational, revenue, and employee performance trends.

This part is editorializing, but Vendr has the opportunity to dig deeper into tech-driven process improvement compared to current automation platforms that focus on documenting and driving process, but have to abstract the technologies used to support the process. In the short term, Vendr has enough work to do in creating the first SaaS Lifecycle Management company that brings buying, expense, and operations management together. But with this level of funding, Vendr has the opportunity to go even further in aligning SaaS to business value not only from a cost-basis perspective, but from a top-line revenue contribution perspective. Needless to say, Amalgam Insights looks forward to seeing Vendr deliver on its vision for managing and supporting SaaS management at scale and to tracking the investments Vendr makes in its people, products, and data ecosystem.