{"id":23127,"date":"2023-01-24T21:31:15","date_gmt":"2023-01-25T00:31:15","guid":{"rendered":"https:\/\/ee02395c61.nxcli.io\/insights\/data-centric\/"},"modified":"2024-04-10T17:57:20","modified_gmt":"2024-04-10T20:57:20","slug":"data-centric-artificial-intelligence","status":"publish","type":"insights","link":"https:\/\/elogroup.com\/en\/insights\/data-centric-artificial-intelligence\/","title":{"rendered":"Data-centric: data at the heart of Artificial Intelligence"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"23127\" class=\"elementor elementor-23127 elementor-16148\" data-elementor-post-type=\"insights\">\n\t\t\t\t\t\t<section data-particle_enable=\"false\" data-particle-mobile-disabled=\"false\" class=\"elementor-section elementor-top-section elementor-element elementor-element-136f53f elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"136f53f\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-ceb0906\" data-id=\"ceb0906\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-e79111b elementor-widget elementor-widget-text-editor\" data-id=\"e79111b\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><strong>By EloInsights<\/strong><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b9abea2 elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"b9abea2\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-fed7655 elementor-widget elementor-widget-text-editor\" data-id=\"fed7655\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul><li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"1\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" aria-setsize=\"-1\" data-aria-posinset=\"1\" data-aria-level=\"1\"><i><span data-contrast=\"auto\">Artificial intelligence (AI) models are already taking organizations to the next level of advanced analytics, merging a data-driven culture.<\/span><\/i><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559737&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/li><li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"1\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" aria-setsize=\"-1\" data-aria-posinset=\"1\" data-aria-level=\"1\"><i><span data-contrast=\"auto\">Against a backdrop of the maturing of companies&#8217; analytical ability, the principle of data-centric AI proposes bringing concern for data quality to the center to evolve AI-based systems.<\/span><\/i><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/li><li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"1\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" aria-setsize=\"-1\" data-aria-posinset=\"1\" data-aria-level=\"1\"><i><span data-contrast=\"auto\">Besides an overview of the topic, the article also presents factors that could affect the future of AI, such as data labelling and causal models.<\/span><\/i><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d91bd21 elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"d91bd21\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-182e02f elementor-widget elementor-widget-text-editor\" data-id=\"182e02f\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span data-contrast=\"auto\">In today&#8217;s business environment, adopting a data-centric culture is fundamental to an organization that aims, not only to remain competitive, but also, to expand its ability to act and deliver value to all the stakeholders involved. To realize a scenario in which decision-making is based on data, it is crucial to invest in key areas such as advanced analytics and artificial intelligence (AI). <\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/p><p><span data-contrast=\"auto\">This means that organizations need to take a few steps back and answer some fundamental questions that concern their foundations. For example: how does the company currently handle its data?\u00a0<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/p><p><span data-contrast=\"auto\">Although discussions around advanced analytics and artificial intelligence evoke scenarios of high technological sophistication, there is earlier groundwork that needs to be done to make this more advanced reality viable. And this is where many companies still fall short.\u00a0<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/p><p><span data-contrast=\"auto\">It is within this scenario that the concept of \u201cdata-centric AI\u201d is born. It proves that does not matter how advanced and mature current AI models may be, it is vital for organizations to have on their horizon the crucial importance of the quality and availability of data so that this work can be done more accurately, thus opening new possibilities for application and business development.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-abaef0a elementor-widget elementor-widget-spacer\" data-id=\"abaef0a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3d93664 elementor-widget elementor-widget-testimonial\" data-id=\"3d93664\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"testimonial.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-testimonial-wrapper\">\n\t\t\t\t\t\t\t<div class=\"elementor-testimonial-content\">\u201cIt is about having very correct data with lots of information and in smaller quantities to get the best performance from the models in relation to what you are trying to answer. That is the remarkable thing about data-centric: an AI in which you work more carefully so that the data can generate good future result\u201d<\/div>\n\t\t\t\n\t\t\t\t\t\t<div class=\"elementor-testimonial-meta\">\n\t\t\t\t<div class=\"elementor-testimonial-meta-inner\">\n\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t<div class=\"elementor-testimonial-details\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"elementor-testimonial-name\">Pedro Guilherme Ferreira<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"elementor-testimonial-job\">Data Science Specialist<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-762cefd elementor-widget elementor-widget-spacer\" data-id=\"762cefd\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f855086 elementor-widget elementor-widget-heading\" data-id=\"f855086\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">What is Data-centric? <\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8e598b1 elementor-widget elementor-widget-text-editor\" data-id=\"8e598b1\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span data-contrast=\"auto\">In 2020, the Cappra Institute interviewed 500 specialists in various companies in Brazil who, on average, dealt with a volume of data close to 10 petabytes, with an expected growth of 175% over the next 5 years. Despite this, only 48% of the employees in these organizations actually used data in decision-making. It is to meet the demand to extract the largest amount of useful information from big data that data-centric AI brings a new perspective: looking at how the data used to train artificial intelligence models is extracted, processed and stored.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/p><p><span data-contrast=\"auto\">Organizations are already channeling resources into AI-based technologies. An <\/span><span style=\"text-decoration: underline;\"><span style=\"color: #0000ff;\"><a style=\"color: #0000ff; text-decoration: underline;\" href=\"https:\/\/mittechreview.com.br\/empresas-da-america-latina-investem-em-dados-e-ia-para-acelerar-negocios\/\" target=\"_blank\" rel=\"noopener\">IDC research<\/a><\/span><\/span><span data-contrast=\"auto\"> concludes that 86% of more than 300 companies analyzed in eight Latin American countries have already adopted Data, Analytics and Artificial Intelligence solutions. This, combined with machine learning, is among the main investments made from 2022 onwards. Another study, from <\/span><span style=\"text-decoration: underline;\"><span style=\"color: #0000ff;\"><a style=\"color: #0000ff; text-decoration: underline;\" href=\"https:\/\/mittechreview.com.br\/papel-estrategico-e-fundamental-na-digitalizacao-a-area-de-ti-nas-empresas-latino-americanas\/\" target=\"_blank\" rel=\"noopener\">Dell in partnership with MIT Technology Review<\/a><\/span><\/span><span data-contrast=\"auto\">, shows that AI is on the horizon for four out of every ten Latin American companies, with the Internet of Things (IoT) appearing in the plans of 34% of organizations.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/p><p><span data-contrast=\"auto\">The plans are promising, but the reality now is different, as companies\u2019 analytical capacity is still low. Proof of this is that the lack of maturity in dealing with data is the main reason for dissatisfaction among analytics professionals, according to <span style=\"text-decoration: underline;\"><span style=\"color: #0000ff;\"><a style=\"color: #0000ff; text-decoration: underline;\" href=\"https:\/\/www.stateofdata.com.br\/_files\/ugd\/e99c65_97b434ed9f1b40bdb3312fccc8cb8bd7.pdf\" target=\"_blank\" rel=\"noopener\">State of Data Brazil 2021<\/a><\/span><\/span>. In other words, to leverage innovation and develop and keep the most talented professionals, it is essential to provide a technology and tools structure, show a clear vision of processes and governance, create a prioritized roadmap of use cases and shape the culture for data-centric based decision-making. And all of this can come at a huge cost.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/p><p><span data-contrast=\"auto\">It is important to first understand the importance of prioritizing the foundation of the data. Even before hiring data scientists or super-specialized engineers to make gains with technologies linked to advanced analytics, such as AI, robustness must be guaranteed. This is the thesis of Pedro Guilherme Ferreira, Data Science Specialist: \u201cIt is essential to have governance that is more concerned with the accuracy of the data in order to be able to make decisions based on it\u201d. <\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/p><p><span data-contrast=\"auto\">Having data-centric AI as a principle reinforces the construction of indicators, since today many industries do not even collect data to structure historical series on which to base predictive models. Bringing data to the center means, for example, applying a metric layer \u2013 a semantic layer or a centralized repository in which data teams define and store business metrics. \u201cThat way, everything you build in Analytics will have a single source, a source of truth for that data\u201d, explains Ferreira.\u00a0<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/p><p><span data-contrast=\"auto\">This does not just refer to storing them in a data lake (a store of structured and unstructured data that allows for different types of analysis and processing of big data), but it concerns how this repository will be built and what will be extracted from it. In a simple example, this means that the way in which the data is described and stored can make an AI-based model for quality control of manufacturing in an industry using image recognition more or less efficiently.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/p><p><span data-contrast=\"auto\">\u201cData-centric is more complex. To start being a data-driven company, you must think more about the data than the model. Data has always been at the heart of analytics and statistics. The concern must be there\u201d, says Ferreira.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-9ab535c elementor-widget elementor-widget-spacer\" data-id=\"9ab535c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-87279ac elementor-widget elementor-widget-testimonial\" data-id=\"87279ac\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"testimonial.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-testimonial-wrapper\">\n\t\t\t\t\t\t\t<div class=\"elementor-testimonial-content\">\u201cIt is essential to have a governance that is more concerned with the accuracy of data to be able to make decisions based on it\u201d<\/div>\n\t\t\t\n\t\t\t\t\t\t<div class=\"elementor-testimonial-meta\">\n\t\t\t\t<div class=\"elementor-testimonial-meta-inner\">\n\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t<div class=\"elementor-testimonial-details\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"elementor-testimonial-name\">Pedro Guilherme Ferreira<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"elementor-testimonial-job\">Data Science Specialist<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-582c665 elementor-widget elementor-widget-spacer\" data-id=\"582c665\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-17d61ef elementor-widget elementor-widget-heading\" data-id=\"17d61ef\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">The evolution of AI models<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b3d438a elementor-widget elementor-widget-text-editor\" data-id=\"b3d438a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span data-contrast=\"auto\">The concept of data-centric AI is new. So much so, that it occupies the first quadrant among the innovations in <\/span><span style=\"text-decoration: underline;\"><span style=\"color: #0000ff;\"><a style=\"color: #0000ff; text-decoration: underline;\" href=\"https:\/\/www.gartner.com\/en\/articles\/what-s-new-in-artificial-intelligence-from-the-2022-gartner-hype-cycle?utm_medium=social&amp;utm_source=linkedin\" target=\"_blank\" rel=\"noopener\">Gartner\u2019s Hype Cycle for AI 2022<\/a><\/span><\/span><span data-contrast=\"auto\"> chart.\u00a0<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/p><p><span data-contrast=\"auto\">In a recent interview for <\/span><span style=\"text-decoration: underline;\"><span style=\"color: #0000ff;\"><a style=\"color: #0000ff; text-decoration: underline;\" href=\"https:\/\/fortune.com\/2022\/06\/21\/andrew-ng-data-centric-ai\/\" target=\"_blank\" rel=\"noopener\">Fortune<\/a><\/span><\/span><span data-contrast=\"auto\">, Andrew Ng, one of the pioneers of deep learning, founder and CEO of Landing AI and a great advocate of data-centric AI, emphasizes the value of data in this context. The premise is that the last generation AI algorithms are increasingly ubiquitous thanks to open-source repositories and the publication of cutting-edge research. Companies can access the same code as giants like Google or NASA, but success will depend on what data is used to train their algorithms and how it is collected and processed \u2013 also on how it is governed. The idea behind the data-centric concept is to create artificial intelligence systems that are well-trained using the smallest possible amount of very well-prepared data.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/p><p><span data-contrast=\"auto\">Ferreira highlights that this understanding is the result of an evolution. \u201cFor a while, everything was very focused on the issue of models. The data came from social media, from giants like Facebook and Google. The focus was on modelling. &#8220;You went from machine learning to other artificial intelligence models, with neural networks\u201d,&#8221; points out the Data Science Specialist.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/p><p><span data-contrast=\"auto\">Following this same line of evolution, we can better understand the proposed shift towards data-centricity. At an early stage, interest centered on the performance and accuracy of AI models. Deep learning has deepened the learning layers of artificial intelligence through more autonomous algorithms within the machining learning process, making it possible to develop adaptive systems that resemble the human brain, neural networks, adding complexity to data analysis models.\u00a0<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/p><p><span data-contrast=\"auto\">In the current discussion, these models are already considered mature and what makes the difference is the quality of the data used to train them. In addition, companies are now able to collect information more independently and process this information in the best possible way to take analyses to the next level.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559685&quot;:0,&quot;335559737&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/p><p><span data-contrast=\"auto\">\u201cIt is about having very correct data with lots of information and in smaller quantities to get the best performance from the models in relation to what you are trying to answer\u201d, reinforces Ferreira. \u201cThat is the great thing about data-centric: an AI in which you work more carefully so that the data can generate good future results\u201d.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/p><p><span data-contrast=\"auto\">As with the application of any technological resource, there is no silver bullet in artificial intelligence. For each problem to be solved, there is a more suitable model. The way it works can involve all types of data, whether it is a text, an image, a time series, etc. Regardless, the model reduces dimensionality to capture the entire structure of what is being analyzed, until there is something left over that cannot be captured. Let\u2019s look at a more concrete example: in an industry, you need to predict the sales of a brand of soft drink in each month. To do so, they use historical sales data.\u00a0<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/p><p><span data-contrast=\"auto\">An AI model can consider various parameters: seasonality, trend, economic cycle and short-term variations, among others. The sales time series can have different profiles: more or less seasonality, for example. Therefore, it is possible to use one artificial intelligence tool to better capture seasonality; another to check on the trend; another model responsible to capture another parameter of interest to put together this history that will form the basis of the predictive model.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/p><p><span data-contrast=\"auto\">The evolution of the model happens when it picks up nuances that earlier versions were unable to. From a predictive model that used linear variations, it evolved to one that analyses non-linearly over time. Or, in a more sophisticated application context, an image recognition system that used to be based on black and white, but now can capture ten colors; another turned able to capture 20 colors. And so go on.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/p><p><span data-contrast=\"auto\">\u201cIn this hypothetical example, we can say that there are already models that pick up all the color spectrums. What is new is that the problem lies in the information used to train artificial intelligence algorithms. If I use distorted, low-quality images, they will have a negative impact on image recognition technology, for example\u201d, states Ferreira, establishing the link with the data-centric principle.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559685&quot;:0,&quot;335559737&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-45c49af elementor-widget elementor-widget-spacer\" data-id=\"45c49af\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5d0439e elementor-widget elementor-widget-testimonial\" data-id=\"5d0439e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"testimonial.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-testimonial-wrapper\">\n\t\t\t\t\t\t\t<div class=\"elementor-testimonial-content\">\u201cTo start being a data-driven company, you have to think more about the data than the model. Data has always been at the heart of analytics and statistics. The concern must be there\u201d<\/div>\n\t\t\t\n\t\t\t\t\t\t<div class=\"elementor-testimonial-meta\">\n\t\t\t\t<div class=\"elementor-testimonial-meta-inner\">\n\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t<div class=\"elementor-testimonial-details\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"elementor-testimonial-name\">Pedro Guilherme Ferreira<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"elementor-testimonial-job\">Data Science Specialist<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2bffcec elementor-widget elementor-widget-spacer\" data-id=\"2bffcec\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-285df5d elementor-widget elementor-widget-heading\" data-id=\"285df5d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">The use of Artificial Intelligence <\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d41dd56 elementor-widget elementor-widget-text-editor\" data-id=\"d41dd56\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span data-contrast=\"auto\">The expansion of artificial intelligence uses on different sectors of the economy, such as industry 4.0, manufacturing or agriculture, does not mean that we want to exclude the evolution of models. The discussion is that, to improve the precision and performance of these models, it is more helpful to priorities the quality of the data, with greater accuracy.\u00a0<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559685&quot;:0,&quot;335559737&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/p><p><span data-contrast=\"auto\">We can think here of the issue of technology bias \u2013 another universe that involves issues such as algorithmic racism. But in the industrial context, if I train with biased or inaccurate information, the algorithm responsible for identifying imperfections in the manufacturing process, even with the best possible code, that AI model will not optimally improve my manufacturing process. Biased data produces biased results.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559685&quot;:0,&quot;335559737&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/p><p><span data-contrast=\"auto\">In this hypothetical scenario, the Internet of Things can be a strong ally. \u201cEvery day, more factories are installing sensors. In addition, we will have cameras that take pictures with more pixels, in better resolution, to feed quality control systems through image recognition. The repository of this data will also have better processing and more tools will be available to help look after the quality of the information\u201d, suggests Pedro Guilherme Ferreira.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559685&quot;:0,&quot;335559737&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/p><p><span data-contrast=\"auto\">As the importance of advanced analytics and AI as a tool for differentiating companies across the entire spectrum of the economy grows rapidly, organizations need to find ways to make data analysis more precise, automated and better able to provide targeted responses to business challenges. Against a backdrop of maturing <span style=\"text-decoration: underline;\"><span style=\"color: #0000ff; text-decoration: underline;\"><a style=\"color: #0000ff; text-decoration: underline;\" href=\"https:\/\/elogroup.com\/en\/insights\/artificial-intelligence-impact-work\/\">AI models<\/a><\/span><\/span>, attention and priorities are gradually turning to the fundamentals of data and the well-known wisdom that, in these cases, quality is more important than quantity.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559685&quot;:0,&quot;335559737&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:360}\">\u00a0<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>In a scenario of maturing companies&#8217; analytical capabilities, the principle of data-centric AI proposes bringing to the center the concern with data quality to evolve AI-based systems.<\/p>\n","protected":false},"author":9,"featured_media":26317,"parent":0,"template":"","editorias":[125],"industrias-category":[126,132,147,142,146,133,148,134,144,149],"praticas-category":[127,153,159,137,156,135],"insights-category":[160],"class_list":["post-23127","insights","type-insights","status-publish","has-post-thumbnail","hentry","editorias-strategically-digital-en","industrias-category-agrobusiness","industrias-category-energia-oleo-gas-en","industrias-category-financial-services","industrias-category-government","industrias-category-healthcare","industrias-category-infraestrutura-en","industrias-category-logistics-and-transportation","industrias-category-manufatura-en","industrias-category-mining","industrias-category-retail","praticas-category-ai-algorithms","praticas-category-data-engineering-big-data-en","praticas-category-digital-products","praticas-category-transformacao-digital-en","praticas-category-hyperautomation-en","praticas-category-estrategia-inovacao-en","insights-category-strategically-digital-en"],"_links":{"self":[{"href":"https:\/\/elogroup.com\/en\/wp-json\/wp\/v2\/insights\/23127","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/elogroup.com\/en\/wp-json\/wp\/v2\/insights"}],"about":[{"href":"https:\/\/elogroup.com\/en\/wp-json\/wp\/v2\/types\/insights"}],"author":[{"embeddable":true,"href":"https:\/\/elogroup.com\/en\/wp-json\/wp\/v2\/users\/9"}],"version-history":[{"count":23,"href":"https:\/\/elogroup.com\/en\/wp-json\/wp\/v2\/insights\/23127\/revisions"}],"predecessor-version":[{"id":24120,"href":"https:\/\/elogroup.com\/en\/wp-json\/wp\/v2\/insights\/23127\/revisions\/24120"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/elogroup.com\/en\/wp-json\/wp\/v2\/media\/26317"}],"wp:attachment":[{"href":"https:\/\/elogroup.com\/en\/wp-json\/wp\/v2\/media?parent=23127"}],"wp:term":[{"taxonomy":"editorias","embeddable":true,"href":"https:\/\/elogroup.com\/en\/wp-json\/wp\/v2\/editorias?post=23127"},{"taxonomy":"industrias-category","embeddable":true,"href":"https:\/\/elogroup.com\/en\/wp-json\/wp\/v2\/industrias-category?post=23127"},{"taxonomy":"praticas-category","embeddable":true,"href":"https:\/\/elogroup.com\/en\/wp-json\/wp\/v2\/praticas-category?post=23127"},{"taxonomy":"insights-category","embeddable":true,"href":"https:\/\/elogroup.com\/en\/wp-json\/wp\/v2\/insights-category?post=23127"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}