{"id":594061,"date":"2025-04-08T08:31:00","date_gmt":"2025-04-08T06:31:00","guid":{"rendered":"https:\/\/www.devoteam.com\/expert-view\/sagemaker-unified-studio-centralised-access-to-data-analytics-ai-and-governance\/"},"modified":"2025-04-08T08:31:00","modified_gmt":"2025-04-08T06:31:00","slug":"sagemaker-unified-studio-centralised-access-to-data-analytics-ai-and-governance","status":"publish","type":"expert-view","link":"https:\/\/devoteam.info\/lu\/expert-view\/sagemaker-unified-studio-centralised-access-to-data-analytics-ai-and-governance\/","title":{"rendered":"SageMaker Unified Studio: Centralised access to data analytics, AI and governance"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\"><strong>SageMaker Unified Studio<\/strong> is a centralised environment that streamlines the use of multiple AWS services. Currently available in preview across nine regions\u2014including Europe (Paris)\u2014it represents a significant step forward in unifying AWS\u2019s data and AI tooling.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Are you an AWS user curious about what the new <strong>SageMaker Unified Studio<\/strong> can do for you? While Amazon SageMaker has traditionally been associated with AI and machine learning, this new unified experience extends its scope to include data processing, analytics, and collaboration.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">I discovered this new interface during an AWS workshop: managed notebooks, direct access to <strong>Redshift<\/strong>, <strong>Athena<\/strong>, and <strong>Bedrock<\/strong>\u2014all integrated into a single environment, offering centralised and secure access to data. It\u2019s a major step toward breaking down silos and simplifying workflows for data professionals.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In this article, I\u2019ll cover:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>The strategic role of SageMaker Unified Studio within the AWS ecosystem<\/li>\n\n\n\n<li>Its core functionalities across machine learning, analytics, and governance<\/li>\n\n\n\n<li>Insights and feedback from my initial hands-on experience<br><\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-sagemaker-unified-studio-in-the-aws-ecosystem\">SageMaker Unified Studio in the AWS ecosystem<\/h2>\n\n\n\n<h3 class=\"wp-block-heading has-medium-font-size\" id=\"h-context\">Context<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">In today\u2019s landscape, where data and AI are at the heart of business strategy, users\u2014whether data engineers, data scientists, or analysts\u2014often need to juggle multiple tools to get their work done.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">On one hand, they rely on services like <strong>Athena<\/strong>, <strong>Redshift<\/strong>, and ETL workflows (such as <strong>Glue Jobs<\/strong> or <strong>Lambda functions<\/strong>) to process, prepare, and analyse data. On the other hand, they turn to platforms like <strong>SageMaker Studio<\/strong> and <strong>Bedrock<\/strong> to train and deploy machine learning models and harness the power of generative AI.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">However, data is often siloed by use case, and AWS services have historically evolved in isolation\u2014without true convergence between data analytics tools and those dedicated to AI. <strong>This is the challenge Amazon aims to solve with SageMaker Unified Studio<\/strong>: an integrated environment designed to accelerate both analytics and machine learning projects in the AWS cloud, while fostering better collaboration across teams and business units.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">By giving users access to the most widely adopted services in its ecosystem\u2014from simple analytics to generative AI and machine learning\u2014<strong>AWS delivers a platform that:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Centralises access to data<\/strong><\/li>\n\n\n\n<li><strong>Facilitates collaboration across diverse roles (data scientists, engineers, analysts)<\/strong><\/li>\n\n\n\n<li><strong>Accelerates end-to-end development of AI solutions<\/strong><strong><br><\/strong><\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">With the integration of <strong>Amazon Q Developer<\/strong>\u2014AWS\u2019s generative AI assistant\u2014SageMaker Unified Studio transforms into a smart, interactive environment. It helps users explore data, generate code and SQL queries, and offers context-aware, personalised guidance throughout the workflow.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-the-new-generation-of-sagemaker\">The New Generation of SageMaker<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">AWS is evolving SageMaker beyond a pure machine learning service. It evolves into a comprehensive <strong>data and AI platform<\/strong> by integrating key services in analytics, artificial intelligence, and governance.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This new generation of SageMaker is built around <strong>four core pillars<\/strong>:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Amazon SageMaker Unified Studio<\/strong>. The subject of this article: a centralised environment for working across analytics and machine learning.<\/li>\n\n\n\n<li><strong>Amazon SageMaker AI<\/strong>. Consolidates all existing SageMaker capabilities for data preparation, model building, training, and deployment.<\/li>\n\n\n\n<li><strong>Amazon SageMaker Lakehouse<\/strong>. A solution for centralising and unifying data from <strong>Amazon S3<\/strong>, <strong>Redshift<\/strong>, and third-party or federated data sources.<br><strong>Amazon SageMaker Data and AI Governance<\/strong>. A secure platform for discovery, governance, and collaboration around data and AI models, powered by <strong>SageMaker Catalog<\/strong> and <strong>Amazon DataZone<\/strong>. <em>(For more details, you can refer <a href=\"https:\/\/devoteam.info\/lu\/expert-view\/sharing-data-across-aws-account-with-amazon-datazone\/\" target=\"_blank\" rel=\"noreferrer noopener\">to this article<\/a>)<br><\/em><\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Among these pillars, <strong>SageMaker Unified Studio<\/strong> stands out by delivering a consistent and unified user experience. It brings together a range of AWS components under one interface\u2014making it easier for <strong>data analysts, engineers, scientists, and even data quality managers<\/strong> to collaborate and access what they need.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"404\" src=\"https:\/\/devoteam.info\/wp-content\/uploads\/2025\/04\/Devoteam_Expert-view_AWS_SageMaker-Unified-Studio-4-1024x404.jpg\" alt=\"Amazon SageMaker Unified Studio\" class=\"wp-image-570231\" style=\"width:800px\" srcset=\"https:\/\/devoteam.info\/wp-content\/uploads\/2025\/04\/Devoteam_Expert-view_AWS_SageMaker-Unified-Studio-4-1024x404.jpg 1024w, https:\/\/devoteam.info\/wp-content\/uploads\/2025\/04\/Devoteam_Expert-view_AWS_SageMaker-Unified-Studio-4-300x118.jpg 300w, https:\/\/devoteam.info\/wp-content\/uploads\/2025\/04\/Devoteam_Expert-view_AWS_SageMaker-Unified-Studio-4-768x303.jpg 768w, https:\/\/devoteam.info\/wp-content\/uploads\/2025\/04\/Devoteam_Expert-view_AWS_SageMaker-Unified-Studio-4-1536x606.jpg 1536w, https:\/\/devoteam.info\/wp-content\/uploads\/2025\/04\/Devoteam_Expert-view_AWS_SageMaker-Unified-Studio-4.jpg 1920w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">The aim is simple: <strong>facilitate access, sharing, and cross-functional collaboration<\/strong> through an intuitive, streamlined interface that adapts to various roles.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">From my perspective, Studio adds clear value in at least three key areas:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Data analysis<\/li>\n\n\n\n<li>AI and machine learning<\/li>\n\n\n\n<li>Data governance and security<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading has-medium-font-size\" id=\"h-1-data-analysis\">1. Data Analysis<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">SageMaker Unified Studio simplifies data exploration and processing by integrating a built-in <strong>SQL Query Editor<\/strong>. This allows users to query and interact with data using familiar AWS services.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">You can directly access <strong>Amazon Athena<\/strong> and <strong>Amazon Redshift<\/strong>, two of AWS\u2019s most widely adopted tools for data analytics:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Amazon Athena<\/strong> is a serverless, interactive service that lets you run SQL queries directly on data stored in <strong>Amazon S3<\/strong>, without having to set up or manage any infrastructure.<\/li>\n\n\n\n<li><strong>Amazon Redshift<\/strong> is a fully managed, petabyte-scale <strong>cloud data warehouse<\/strong> designed for high-performance querying and large-scale analytics.<\/li>\n<\/ul>\n\n\n\n<figure class=\"wp-block-image size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"579\" src=\"https:\/\/devoteam.info\/wp-content\/uploads\/2025\/04\/Devoteam_Expert-view_AWS_SageMaker-Unified-Studio-1-1024x579.png\" alt=\"Amazon SageMaker Unified Studio\" class=\"wp-image-570247\" style=\"width:800px\" srcset=\"https:\/\/devoteam.info\/wp-content\/uploads\/2025\/04\/Devoteam_Expert-view_AWS_SageMaker-Unified-Studio-1-1024x579.png 1024w, https:\/\/devoteam.info\/wp-content\/uploads\/2025\/04\/Devoteam_Expert-view_AWS_SageMaker-Unified-Studio-1-300x170.png 300w, https:\/\/devoteam.info\/wp-content\/uploads\/2025\/04\/Devoteam_Expert-view_AWS_SageMaker-Unified-Studio-1-768x434.png 768w, https:\/\/devoteam.info\/wp-content\/uploads\/2025\/04\/Devoteam_Expert-view_AWS_SageMaker-Unified-Studio-1.png 1394w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">From within the Studio, both services are accessible with a simple click\u2014just use the contextual menu (three dots) next to any table to launch a query, making data retrieval seamless and intuitive.<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-medium-font-size\" id=\"h-2-ai-and-machine-learning\">2. AI and Machine Learning<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">SageMaker Unified Studio provides everything needed to build, train, and deploy machine learning models\u2014all within a single interface:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Interactive environments<\/strong>: Users can launch <strong>JupyterLab<\/strong>, a web-based development environment ideal for writing, organising, and running ML notebooks and workflows.<br><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Accessible LLMs<\/strong>: When setting up an environment, users can choose from a range of <strong>foundation models<\/strong> available via <strong>Amazon Bedrock<\/strong>, simplifying experimentation with generative AI.<br><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>AI-powered assistance<\/strong>: With <strong>Amazon Q Developer<\/strong> integrated directly into the Studio, users can ask questions in natural language, explore datasets, and generate code or SQL queries\u2014making data exploration easier and more intuitive.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"563\" src=\"https:\/\/devoteam.info\/wp-content\/uploads\/2025\/04\/Devoteam_Expert-view_AWS_SageMaker-Unified-Studio-2-1024x563.png\" alt=\"\" class=\"wp-image-570263\" style=\"width:800px\" srcset=\"https:\/\/devoteam.info\/wp-content\/uploads\/2025\/04\/Devoteam_Expert-view_AWS_SageMaker-Unified-Studio-2-1024x563.png 1024w, https:\/\/devoteam.info\/wp-content\/uploads\/2025\/04\/Devoteam_Expert-view_AWS_SageMaker-Unified-Studio-2-300x165.png 300w, https:\/\/devoteam.info\/wp-content\/uploads\/2025\/04\/Devoteam_Expert-view_AWS_SageMaker-Unified-Studio-2-768x422.png 768w, https:\/\/devoteam.info\/wp-content\/uploads\/2025\/04\/Devoteam_Expert-view_AWS_SageMaker-Unified-Studio-2-1536x844.png 1536w, https:\/\/devoteam.info\/wp-content\/uploads\/2025\/04\/Devoteam_Expert-view_AWS_SageMaker-Unified-Studio-2.png 1999w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Generative AI application development<\/strong>: SageMaker Studio also facilitates the creation and scaling of <strong>generative AI applications<\/strong> powered by <strong>Bedrock<\/strong> and supported by scalable infrastructure.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"579\" src=\"https:\/\/devoteam.info\/wp-content\/uploads\/2025\/04\/Devoteam_Expert-view_AWS_SageMaker-Unified-Studio-1-1024x579.png\" alt=\"Amazon SageMaker Unified Studio\" class=\"wp-image-570247\" style=\"width:800px\" srcset=\"https:\/\/devoteam.info\/wp-content\/uploads\/2025\/04\/Devoteam_Expert-view_AWS_SageMaker-Unified-Studio-1-1024x579.png 1024w, https:\/\/devoteam.info\/wp-content\/uploads\/2025\/04\/Devoteam_Expert-view_AWS_SageMaker-Unified-Studio-1-300x170.png 300w, https:\/\/devoteam.info\/wp-content\/uploads\/2025\/04\/Devoteam_Expert-view_AWS_SageMaker-Unified-Studio-1-768x434.png 768w, https:\/\/devoteam.info\/wp-content\/uploads\/2025\/04\/Devoteam_Expert-view_AWS_SageMaker-Unified-Studio-1.png 1394w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<h3 class=\"wp-block-heading has-medium-font-size\" id=\"h-3-data-governance-and-security\">3. Data Governance and Security<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Governance and security are key pillars of SageMaker Unified Studio, ensuring that data access and usage remain secure and compliant:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Data Catalog<\/strong>: Based on <strong>Amazon DataZone<\/strong>, the <strong>SageMaker Catalog<\/strong> enables metadata management, schema discovery, and dataset exploration. Users can easily browse available datasets and understand their structure before usage.<br><\/li>\n\n\n\n<li><strong>Access control and sharing<\/strong>: The environment leverages <strong>IAM<\/strong> and <strong>Lake Formation<\/strong> to define fine-grained access controls. Each user only sees the resources they are authorised to access, ensuring secure collaboration and compliance with internal security policies.<br><\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">By combining these features, <strong>SageMaker Unified Studio creates a unified and secure space for working across data analysis, machine learning, and governance workflows<\/strong>\u2014streamlining collaboration and accelerating delivery across teams.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-my-feedback-on-sagemaker-unified-studio\">My Feedback on SageMaker Unified Studio<\/h2>\n\n\n\n<h3 class=\"wp-block-heading has-medium-font-size\" id=\"h-a-unified-ide-for-business-oriented-profiles\">A Unified IDE for Business-Oriented Profiles<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">One of <strong>SageMaker Unified Studio&#8217;s<\/strong> main strengths is its <strong>fully integrated<\/strong> <strong>approach.<\/strong> There&#8217;s no longer a need to navigate across multiple AWS services\u2014everything is accessible from a single, centralised environment. Whether for data analysis, transformation, governance, or AI\/ML usage, all the necessary tools are brought together into one seamless interface.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This simplification greatly benefits data and AI teams by <strong>removing the overhead of interconnecting services<\/strong> and by promoting easier, more secure <strong>collaboration and data sharing<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">From my perspective, SageMaker Unified Studio is positioned as more than a development environment\u2014<strong>an enhanced IDE++<\/strong> designed to streamline analysis, data mining, and AI tools across teams.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The integration of <strong>Amazon Q Developer<\/strong>, AWS\u2019s generative AI assistant, reinforces this positioning. It brings clear value when it comes to <strong>simple data exploration or SQL generation<\/strong>, making the platform even more accessible to business profiles. However, for more complex queries or production-grade automation, <strong>human oversight remains essential<\/strong>. While helpful, Amazon Q still has limitations in terms of robustness and precision.<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-medium-font-size\" id=\"h-for-whom-is-it-best-suited\">For Whom Is It Best Suited?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">In my view, this environment is particularly well-suited for <strong>profiles that are less focused on infrastructure and low-level development<\/strong>. Thanks to its user-friendly interfaces\u2014like the <strong>Query Editor<\/strong>, <strong>chat-based exploration<\/strong>, <strong>governance tools<\/strong>, and <strong>data-sharing features<\/strong>\u2014I see it appealing especially to:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Data Scientists and Analysts<\/strong> seeking quick and secure access to data<\/li>\n\n\n\n<li><strong>Business-oriented users<\/strong> who may not be fluent in infrastructure-as-code and prefer working with visual tools and conversational assistants<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Meanwhile, more technical users\u2014such as platform engineers or backend developers\u2014will likely continue using traditional AWS services, managed through infrastructure-as-code (IaC) tools like Terraform, CloudFormation, or the AWS CLI.<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-medium-font-size\" id=\"h-a-word-of-caution-on-pricing\">A Word of Caution on Pricing<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">While SageMaker Unified Studio offers a compelling integrated experience, <strong>cost management is an area to approach carefully<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Although the Studio itself is free to use, as AWS clearly notes:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">\u201c<em>Each AWS service that you use through the SageMaker Unified Studio is subject to its own individual pricing. This includes AWS storage and compute services, as well as any third-party services, like Git providers. There is no separate cost for using SageMaker Unified Studio itself.<\/em>\u201d<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In addition, when using the <strong>Quick setup option<\/strong>, AWS warns:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">\u201c<em>Here is an additional charge for any networking resources that AWS sets up on your behalf if you choose the <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker-unified-studio\/latest\/adminguide\/create-domain-sagemaker-unified-studio-quick.html\" target=\"_blank\" rel=\"noreferrer noopener\">quick setup option<\/a> for domain creation, and exact costs depend on account configuration. Delete any unused resources to avoid unnecessary costs. For full visibility into costs during the domain creation process, follow the <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker-unified-studio\/latest\/adminguide\/create-domain-sagemaker-unified-studio-manual.html\" target=\"_blank\" rel=\"noreferrer noopener\">manual setup option<\/a>.<\/em>\u201d<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In other words, to <strong>avoid unexpected charges<\/strong>, it\u2019s important to:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Understand the pricing models of the services you interact with (ex: <strong>Athena<\/strong>, <strong>Redshift<\/strong>, etc.)<\/li>\n\n\n\n<li>Prefer the <strong>Manual setup<\/strong> option when deploying a new Studio domain<\/li>\n\n\n\n<li>Monitor and clean up unused resources (notebooks, compute environments, networking, etc.)<br><\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading has-medium-font-size\" id=\"h-final-thoughts\">Final Thoughts<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">SageMaker Unified Studio provides a <strong>modern, collaborative, and intuitive environment<\/strong> that lowers the barrier to entry for many data\u2014and AI-centric roles while still offering power and flexibility. For organisations looking to unify their analytics and ML workflows under a single roof, it\u2019s a promising step forward\u2014<strong>as long as cost optimisation and technical governance are kept in mind.<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"<p>SageMaker Unified Studio is a centralised environment that streamlines the use of multiple AWS services. Currently available in preview across nine regions\u2014including Europe (Paris)\u2014it represents a significant step forward in unifying AWS\u2019s data and AI tooling. Are you an AWS user curious about what the new SageMaker Unified Studio can do for you? While Amazon [&hellip;]<\/p>\n","protected":false},"featured_media":81621,"template":"","categories":[905,1628],"tags":[],"industry":[],"class_list":["post-594061","expert-view","type-expert-view","status-publish","has-post-thumbnail","hentry","category-ai","category-aws"],"acf":[],"cards":"\n\t<div class=\"single-post-card\">\n\n\t\t<figure class=\"wp-block-post-featured-image\"><a href=\"https:\/\/devoteam.info\/lu\/expert-view\/sagemaker-unified-studio-centralised-access-to-data-analytics-ai-and-governance\/\" target=\"_self\" ><img width=\"2560\" height=\"1707\" src=\"https:\/\/devoteam.info\/wp-content\/uploads\/2024\/11\/GettyImages-1399150019.jpg\" class=\"attachment-post-thumbnail size-post-thumbnail wp-post-image\" alt=\"SageMaker Unified Studio: Centralised access to data analytics, AI and governance\" style=\"aspect-ratio:4\/3;width:100%;object-fit:cover;\" decoding=\"async\" loading=\"lazy\" srcset=\"https:\/\/devoteam.info\/wp-content\/uploads\/2024\/11\/GettyImages-1399150019.jpg 2560w, https:\/\/devoteam.info\/wp-content\/uploads\/2024\/11\/GettyImages-1399150019-300x200.jpg 300w, https:\/\/devoteam.info\/wp-content\/uploads\/2024\/11\/GettyImages-1399150019-1024x683.jpg 1024w, https:\/\/devoteam.info\/wp-content\/uploads\/2024\/11\/GettyImages-1399150019-768x512.jpg 768w, https:\/\/devoteam.info\/wp-content\/uploads\/2024\/11\/GettyImages-1399150019-1536x1024.jpg 1536w, https:\/\/devoteam.info\/wp-content\/uploads\/2024\/11\/GettyImages-1399150019-2048x1366.jpg 2048w\" sizes=\"auto, (max-width: 2560px) 100vw, 2560px\" \/><\/a><\/figure>\n\n\t\t\n\t\t<div class=\"wp-block-group is-vertical is-layout-flex wp-container-core-group-is-layout-43282307 wp-block-group-is-layout-flex\">\n\t<p style=\"font-style:normal;font-weight:700\" class=\"has-link-color wp-elements-1 wp-block-lp-post-type has-text-color has-primary-color has-small-font-size\">Expert 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