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

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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.


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.


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.


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,, Informatica, KNIME, Matillion, Okera, Snowflake, Yellowbrick)

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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.


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, 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 Expands Snowflake Partnership continues to grow its Snowflake partnership. Users are able to use machine learning capabilities on the data within their Snowflake environment; 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.

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June 10: From BI to AI (Amazon SageMaker, Databricks, Dataiku, DataRobot,, Google Cloud, Immuta, Informatica, KNIME, Labelbox, Matillion, Neo4j, NVIDIA, Qlik, RapidMiner, Snowflake, Teradata, TIBCO)

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


Immuta Raises $100 Million Series E Round

On June 8, secure data access platform Immuta announced that it had raised $100M in Series E funding. NightDragon led the round, with participation from new investor Snowflake Ventures, and prior investors Dell Technologies Capital, DFJ Growth, IAG, Intel Capital, March Capital, StepStone, Ten Eleven Ventures, and Wipro Ventures. Immuta will use the funds for additional hiring in sales, marketing, and customer success, as well as continued R+D and building out strategic partnerships with other vendors in the cloud data space.

Matillion Reveals Strategic Investment from Citi Ventures

Enterprise cloud data integration platform Matillion announced a strategic investment from Citi Ventures this week for an undisclosed amount. Matillion’s last publicly shared valuation was $1.5B, after their series E round last September for $150M.

Launches, Updates, and Partnerships

Databricks Delivers Data Lineage For Unity Catalog

Databricks announced that data lineage for Unity Catalog is now available in preview on AWS and Microsoft Azure. The data lineage feature will let customers understand the history of any data in their lakehouse – where it came from, when was it created, who created it, how has it been modified from the original raw data import, and how it’s being used, among other features. Because this is done automatically, the results save time and provide better accuracy compared to manually tagging data with the relevant metadata, and allow organizations to better meet compliance standards and relevant regulations.

Dataiku Arrives on Azure

Dataiku announced a partnership with Microsoft Azure this week, launching the Dataiku cloud AI platform in the Azure cloud. Dataiku’s new cloud stack accelerator capability allows for automated deployment, configuration, and management of Dataiku’s Everyday AI platform on Azure with a template-based approach.

DataRobot Debuts AI Cloud Improvements at DataRobot AIX 2022

At DataRobot AIX 2022, DataRobot announced a number of improvements to their AI Cloud product. Notable enhancements include code-first notebooks integrated into AI Cloud, bringing capabilities from the recent Zepl acquisition into DataRobot’s offerings and augmenting support for code-centric data scientists; expanded enterprise-level MLOps capabilities for the full model lifecycle, including integrations with GitHub, SumoLogic, Splunk, Datadog, and Zendesk; bias mitigation that automatically identifies and adapts machine learning models exhibiting detectable bias prior to deployment; and automated compliance documentation, even for models built outside of DataRobot. DataRobot also broadened their partnership with Google Cloud, launching AI Cloud in the Google Cloud Marketplace. Imports Its Natural Language Capabilities to Qlik announced this week that it has joined the Qlik Technology Partner Program. Qlik users will be able to use language intelligence within Qlik Cloud, including natural language capabilities such as sentiment analysis, document categorization, and text disambiguation.

New Features and Partnerships for Google Cloud Vertex AI

At this week’s Google Cloud Applied ML Summit, Google revealed numerous new features and partnerships for their applied machine learning product, Vertex AI. Google’s existing NVIDIA partnership yielded one-click deploy of NVIDIA AI solutions to Vertex AI Workbench, as well as the new Vertex AI Training Reduction Server, which optimizes multi-node distributed training on NVIDIA GPUs, reducing training time for large language models like BERT. Google also announced a new data partnership with Neo4j, allowing data scientists to work with data and build models in Neo4j Graph Data Science, then deploy the models using Vertex AI. One more partnership with Labelbox provided yet another integration, reducing the time required to label unstructured data and speed up the model development process. Finally, Google also announced the preview of several standalone features: Vertex AI Tabular Workflows, allowing users to choose which parts of the model building and deployment processes they want to use AutoML for while being more hands-on with other parts; Serverless Spark for Vertex AI Workbench for data scientists to launch a server less spark session within a notebook; and Vertex AI Example-Based Explanations, which helps data scientists diagnose issues in their models using explainable AI techniques.

Informatica Updates Global Partner Program with Three Initiatives

Informatica revealed enhancements for its Global Channel Partner Program this week to boost partnered sales and support efforts for cloud modernization with joint customers. The new initiatives include incentives to source bookings for Gold and Platinum-level partners; sales, delivery, and technical certifications to help partners in their engagements with joint customers; and a points-based Channel Rewards program to recognize individuals for their contributions.

KNIME Announces Strategic Partnership with Snowflake

Open source data science company KNIME announced a strategic partnership with Snowflake. Users will be able to use the low/no-code KNIME Analytics Platform to perform analytics on data stored in Snowflake.

RapidMiner Releases New Version of Cloud Platform

RapidMiner announced the release of a new version of their data science platform. The latest version marks a move to the cloud as a multi-tenant, SaaS offering.

Teradata Vantage with Amazon SageMaker Launches

Enterprise data platform Teradata introduced Teradata Vantage, a multi-cloud analytics platform integrated with machine learning service Amazon SageMaker. The partnership will allow Teradata customers to access machine learning capabilities via Amazon and apply it to data and analytics hosted on Teradata.


TIBCO Analytics Forum 2022 to Occur June 13-15

TIBCO Analytics Forum (TAF) returns June 13-15, 2022. The online-only event has a theme of “Analytics in Time and Space.” Featured speakers include Ben Shneiderman, computer science professor and founding director of the Human-Computer Interaction Laboratory at the University of Maryland; data visualization guru Nadieh Brehmer; David Baltar Boilève, data scientist at Hospital Universitario Lucus Augusti; Mark Lora, director of enterprise data systems, Taylor University; and Birchcliff Energy analytics engineer Monica Brookwell, among others. To register for the event, please visit TAF 2022

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June 3: From BI to AI (, Gigasheet, Incorta, One AI, Oracle, Rockset, Saturn Cloud)

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Gigasheet Raises $7M Series A Round

Gigasheet, a no-code analytics platform, announced that they had secured $7M in Series A funding. Participants in the funding round included Accomplice, Argon, Founder Collective, and REV, along with individual investors. The funds will go towards filling out their product road map and expanding their future enterprise offering.

One AI Announces $8M Seed Round, Launches NLP-as-a-Service

One AI, a natural language processing provider, announced that they had raised $8M in seed funding from angel investors. Along with the funding, One AI emerged from stealth, launching their NLP-as-a-Service offering. Their Language Skills API includes a number of NLP models for specific business use cases such as conversation and article summarization, clustering and text analytics, and emotion and sentiment extraction, among others. Developers will be able to use these models to transform unstructured text into structured data.

Launches and Updates

Incorta Integrates Delta Sharing, Data Apps

Incorta, a realtime analytics platform, debuted new capabilities this week. Among the new features are a native Delta Sharing integration, allowing Incorta customers to securely share operational data more quickly. Incorta also launched several data apps that acquire operational data from source systems and prepare it for analysis, with already-built business schemas and dashboards for Oracle EBS, Oracle ERP and EPM Clouds, Netsuite, SAP, and others.

Rockset Reveals Oracle Integration

Analytics platform Rockset announced a new integration with Oracle this week, allowing developers to run search, aggregations, and joins on data from Oracle databases in real time. Rockset ingests change data capture streams from Oracle, enabling swift analytical queries.

Saturn Cloud and Announce Partnership to Make Python Analytics More Performant

Data science and machine learning platform Saturn Cloud and parallel data compute platform have launched a partnership. software running within Saturn Cloud resources will allow data scientists to scale up their model prototypes to “petabyte-scale parallel processing production” without requiring tuning or re-coding a model for scaling.