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Solutions Review Executive Editor Tim King curated this list of notable analytics and data science news for the week of March 13, 2026.<\/strong><\/em><\/p>\n Keeping tabs on all the most relevant analytics and data science news can be a time-consuming task. As a result, our editorial team aims to provide a summary of the top headlines from the last week in this space. Solutions Review editors will curate vendor product news, mergers and acquisitions, venture capital funding, talent acquisition, and other noteworthy analytics and data science news items.<\/p>\n For early access to all the expert insights published on Solutions Review<\/em>, join Insight Jam<\/em><\/a><\/strong><\/span>, a community dedicated to enabling the human conversation on AI.<\/p>\n Alteryx Crosses $1B ARR As Customers Lean On Alteryx One As An AI Logic Layer<\/strong><\/p>\n Alteryx has surpassed $1 billion in ARR and now runs more than 380 million automated workflows annually, underscoring how customers are using Alteryx One as a governed logic layer for AI-ready data and analytics. Nearly half of leaders in its new research cite high-quality, accessible, well-governed data as the top requirement for AI success, and Alteryx positions its visual, repeatable workflows as the foundation that captures business logic, preserves lineage, and produces AI-ready outputs at enterprise scale. The company is also simplifying editions and expanding cloud partnerships, including a deeper Google Cloud integration, to make its AI and automation capabilities easier to adopt across modern data platforms.<\/p>\n Read on for more\u2192\u00a0https:\/\/www.prnewswire.com\/news-releases\/alteryx-accelerates-its-next-phase-of-growth-with-ai-ready-data-and-automation-at-enterprise-scale-302707688.html<\/span><\/a><\/span><\/p>\n Databricks\u2019 Genie Code Turns Agentic Coding Loose On Data Engineering And ML Ops<\/strong><\/p>\n Databricks has unveiled Genie Code, an agentic AI assistant for data teams that can design and build pipelines, debug failures, create dashboards, and maintain production systems across the Databricks platform. Unlike generic code agents, Genie Code is wired into Unity Catalog, MLflow 3.0, and Model Serving so it understands lineage, usage, and business semantics and can treat observability as a first-class task\u2014spotting issues and proposing fixes, not just writing code. Databricks also announced its acquisition of Quotient AI to embed continuous evaluation and reinforcement learning directly into Genie and Genie Code for safer, more reliable agent behavior.<\/p>\n Read on for more\u2192\u00a0https:\/\/www.databricks.com\/blog\/introducing-genie-code<\/span><\/a><\/span><\/p>\n Futurum: Dataiku Rebrands As \u201cThe Platform For AI Success\u201d To Govern A Multi-Cloud Agent Wilderness<\/strong><\/p>\n Futurum Group\u2019s Brad Shimmin argues that Dataiku has \u201cshed its skin\u201d as a classic data science workbench and repositioned as \u201cThe Platform for AI Success,\u201d focused on orchestrating and governing AI agents across AWS, Snowflake, Databricks, and beyond. New capabilities include Dataiku Agent Management, a cross-platform control plane that monitors agent behavior and policy alignment; Dataiku Cobuild, which turns natural-language descriptions into orchestrated workflows; and Dataiku Reasoning Systems, domain templates for complex, multi-step operations. The analysis frames Dataiku\u2019s pivot as a move above the compute layer, competing for the \u201cgovernance dollar\u201d by becoming an agnostic control tower for distributed agents rather than yet another model host.<\/p>\n Read on for more\u2192\u00a0https:\/\/futurumgroup.com\/insights\/dataiku-pivots-to-ai-success-can-one-control-plane-master-a-multi-cloud-agent-wilderness\/<\/span><\/a><\/span><\/p>\n DataStrike Expands Fabric Services To De-Risk Fast Moves Into Microsoft\u2019s Unified Analytics Stack<\/strong><\/p>\n DataStrike is expanding its Microsoft Fabric services with three engagement models\u2014Fabric Readiness & POC, Fabric Migration Services, and Fabric Managed Services\u2014to help organizations adopt Fabric for analytics and AI without creating a new tangle of technical debt. The firm offers two-week POCs with real data and use cases, architecture and governance design, capacity planning, and performance validation, followed by structured migrations that cover OneLake design, ingestion, Data Factory pipelines, Synapse modeling, Power BI, and AI\/ML enablement. Ongoing managed services keep Fabric environments tuned for cost, performance, and evolving business needs as organizations shift more analytics and agentic workloads onto the platform.<\/p>\n Read on for more\u2192\u00a0https:\/\/www.datastrike.com\/blogs\/datastrike-expands-microsoft-fabric-services-to-help-organizations-move-faster-with-analytics-and-ai<\/span><\/a><\/p>\n ThoughtSpot\u2019s Spotter Semantics Aims To Be The Agentic Semantic Layer For Analytics<\/strong><\/p>\n ThoughtSpot has launched Spotter Semantics, an AI-native semantic layer built to translate natural language queries from humans and agents into deterministic, context-aware SQL on governed data. The platform uses knowledge-graph-backed semantics, AI-powered indexing, and patented search tokens to encode business logic, security, metrics, cohorts, and synonyms into a machine-readable format that reduces hallucinations and misinterpretation. Analysts can define custom metrics and formulas via a visual UI while CI\/TML pipelines manage deployment, giving organizations a shared, trusted context layer for Spotter agents and other AI consumers.<\/p>\n Read on for more\u2192\u00a0https:\/\/www.thoughtspot.com\/press-releases\/thoughtspot-introduces-spotter-semantics-to-bring-trust-and-context-to-enterprise-ai<\/span><\/a><\/p>\n Insight Jam<\/em> is Getting Set to Host Donald Farmer for the Expert Briefing: The Last Mile to AI & Why Analytics Leadership Matters on March 31<\/strong><\/p>\n While AI can generate insights at unprecedented speed and scale, it cannot verify those insights against business reality, interpret them within organizational context, or take accountability when decisions go wrong. That responsibility still belongs to people. In this live Insight Jam<\/em> session, Donald Farmer introduces the concept he calls the last mile<\/i>: the critical gap between AI-generated output and trustworthy business action.<\/span><\/p>\n Register free on LinkedIn<\/a><\/p>\n Thought Leaders: The Missing Piece in Olympic Analysis by Dr. Joe Perez<\/strong><\/p>\n The most resonant data stories expand the frame without blurring the subject. Diplomas help us do exactly that. They encourage restraint in color and type, transparency in timelines, completeness in counts, respect for institutional context, and generosity toward the broader field of excellence. They remind us that sometimes the smallest artifact carries the biggest structural insight.<\/p>\n Read on Solutions Review<\/em><\/a><\/p>\n Thought Leaders: The Five Stages of Data and AI Strategy Grief by Samir Sharma<\/strong><\/p>\n I\u2019ve been working with a number of clients from one end of the spectrum to the other. Greenfield to Brownfield to spendhugeamountsofmoneyfield! What I have seen in the latter two is that many of these organizations do not struggle with Data & AI because they lack ambition, it\u2019s mainly down to the fact that they confuse investment with impact.<\/p>\n Read on Solutions Review<\/em><\/a><\/p>\n The Editors Lens: The AI-Native Analytics Stack & How AI is Evolving BI in Real-Time<\/strong><\/p>\n The\u00a0best data analytics and BI platforms<\/a><\/strong>\u00a0were traditionally designed around a simple premise: data is collected, transformed,\u00a0visualized<\/a><\/strong>, and interpreted by humans who ultimately make the decisions. Dashboards, reports, and ad-hoc queries formed the center of the analytics experience. Analysts explored data, business leaders consumed the output, and insights moved slowly through organizations as human interpretation translated information into action. That model is now beginning to break.<\/p>\n Read on Solutions Review<\/em><\/a><\/p>\n Contributor Series: Why Workforce Planning is Now Central to Modern FP&A by BARC’s\u00a0 Kelley Lynn Kassa<\/strong><\/p>\n My\u00a0previous\u00a0role as a consultant\u00a0gave me the opportunity to write case studies in the corporate performance management\u00a0(CPM)\u00a0market.\u00a0The overwhelming majority of them\u00a0show that most organizations have implemented\u00a0unique and customized models for\u00a0workforce\u00a0and\/or\u00a0headcount planning.\u00a0<\/span>\u00a0<\/span><\/p>\n Read on Solutions Review<\/em><\/a><\/p>\n Contributor Series: On Combining the Use of AI with Critical Thinking by Professor Dave Cameron<\/strong><\/p>\n It is easy to tell tools such as Claude, or even ChatGPT, to create a Python program that predicts optimal spend using the objectives above, and explain the content of each of the inputs used to predict. For instance, past spend is certainly a predictor of future spend.<\/p>\n Read on Solutions Review<\/em><\/a><\/p>\n –<\/p>\n Insight Jam<\/em> Launches Mesh Lab Episode 2 to Build a Framework for Work & Learning in the Age of AI: The Human Advantage<\/strong><\/p>\n Insight Jam<\/em> Mesh Lab is a year-long, monthly series of expert-led discussions<\/a><\/strong><\/span> dedicated to exploring and shaping the next generation of frameworks for work and learning in the age of AI. Rather than reacting to tools or trends, Mesh Lab is designed to initiate a sustained, cross-sector conversation about how human capability itself must be re-architected as AI becomes embedded across education, enterprise, and leadership.<\/p>\n Watch on Insight Jam<\/em><\/a><\/p>\n Solutions Review <\/i>Surpasses 250K on YouTube to Power Unmatched Media Momentum in Enterprise Tech & the Human Impact of AI<\/b><\/p>\n Solutions Review<\/em>\u00a0has officially surpassed\u00a0250,000 subscribers on YouTube<\/a><\/strong>, a milestone that\u2019s about more than just the number. This moment marks the payoff of a deliberate, two-year strategy\u00a0centered on authoritative video<\/a><\/strong>,\u00a0human-led insight<\/a><\/strong>, and an early recognition of how AI search engines ingest information, assign trust, and surface sources at scale.<\/p>\n Read on Solutions Review<\/em><\/a><\/p>\n Solutions Review<\/em> Editors Launch New ‘Human-AI Ledger’ Newsletter to Chronicle the Human Impact of AI<\/strong><\/p>\n Artificial intelligence is everywhere\u2014but understanding its human impact has never been more urgent. That’s where Solutions Review<\/em>‘s latest newsletter, The Human-AI Ledger<\/i><\/a><\/strong><\/span>, comes in. Designed to chronicle how AI is reshaping the way we learn, work, lead, and live, this newsletter explores the soft side of AI\u2014the non-technical, deeply human dimensions that determine whether this technological revolution helps us thrive or leaves us behind.<\/span><\/p>\nAnalytics and Data Science News for the Week of March 13<\/strong>, 2026<\/strong><\/h2>\n
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<\/a>Watch this space each week as our editors will share upcoming events, new thought leadership, and the best resources from Insight Jam<\/em>, Solutions Review’s enterprise tech community<\/a><\/strong><\/span> where the human conversation around AI is happening. The goal? To help you gain a forward-thinking analysis and remain on-trend through expert advice, best practices, predictions, and vendor-neutral software evaluation tools.<\/p>\n