{"id":34062,"date":"2023-12-02T04:00:00","date_gmt":"2023-12-02T12:00:00","guid":{"rendered":"https:\/\/insidebigdata.com\/?p=34062"},"modified":"2023-12-02T10:24:44","modified_gmt":"2023-12-02T18:24:44","slug":"three-roadblocks-to-using-data-to-its-full-potential","status":"publish","type":"post","link":"https:\/\/insidebigdata.com\/2023\/12\/02\/three-roadblocks-to-using-data-to-its-full-potential\/","title":{"rendered":"Three Roadblocks to Using Data to Its Full Potential"},"content":{"rendered":"\n

Nearly every company is striving to become a better user of its data and make more informed decisions across the organization, and the cloud computing and technology sectors have exploded as platform providers try to make that vision a reality. So why, then, do only 24% of executives view their companies as being data-driven, and just 13% of executives believe their organizations are delivering on their data strategy?<\/a><\/p>\n\n\n\n

Considering that we\u2019re now in a modern data era where we\u2019re discussing advanced data concepts like LLMs, some businesses thrive on not just collecting data, but striving to turn it into a strategic asset. Despite advances in techniques like neural networks and machine learning models, it\u2019s surprising that only a small percentage of companies consider themselves fully data-driven. This inconsistency is not an anomaly, but rather a sign of significant, structural obstacles. The reason? These three major roadblocks that keep companies from tapping into the full potential of their data. <\/p>\n\n\n\n

1. Isolated Environments for Data Quality: <\/strong><\/p>\n\n\n\n

Many ETL tools and data warehousing solutions have built-in data validation features, but they often exist as separate functions and do not cater to enterprise-wide data quality checks. Imagine a smart home system where each device is made by a different manufacturer. Your advanced lighting system doesn\u2019t communicate with your top-of-the-line coffee maker. You may get great individual performances, but the lack of coordination turns your \u2018smart\u2019 home into a missed opportunity.<\/p>\n\n\n\n

It is highly advisable to seek a comprehensive data quality solution that can efficiently address a wide range of your data quality requirements. These may include validating both business and technical rules, facilitating reconciliation processes, conducting data profiling, offering a user-friendly interface with a gentle learning curve, providing seamless integration with various tools, and expeditiously delivering substantial business value at a large scale.<\/p>\n\n\n\n

2. Handle large data volumes:<\/strong><\/p>\n\n\n\n

As businesses deal with larger and larger volumes of data, many still use old-fashioned methods like random sampling for validation, semi-automated scripts \u2014 a technique that is inadequate for today\u2019s needs. It\u2019s like using a rowboat to cross the Atlantic when you have access to cargo ships with the latest navigation systems. You\u2019ll eventually get there, but you\u2019ll waste time, energy, and resources.<\/p>\n\n\n\n

Today, the speed and other technologies that are available means that users can validate and identify exact mismatches across entire datasets at lightning speed. Use modern technologies, especially those powered by AI and machine learning. These can sort through vast amounts of data in real-time, validating, flagging, and enriching information, laying the groundwork for a strong, data-driven strategy. Now, instead of extraneous manual effort, organizations can take any dataset and rest assured that it\u2019ll be tagged and flagged if it doesn\u2019t follow set business rules. By relying on sophisticated distributed computing frameworks that are able to validate datasets much more quickly and effectively, companies can begin to put data to work.<\/p>\n\n\n\n

3. A ballooning number of tools at our disposal:<\/strong><\/p>\n\n\n\n

The market is crowded with tools designed for highly specific tasks, leaving companies with a fragmented and often ineffective set of tools. For the most part, these new technologies have popped up to address singular pain points: one is suited for only data transfers, one only for transformations, one only for streaming, and the list goes on. Imagine a Swiss Army knife where each blade can do one task very well but can\u2019t work together with the others. What you need is not a collection of separate blades, but a truly multi-functional tool, which pulls numerous features under one umbrella to facilitate better integrations and more streamlined processes. <\/p>\n\n\n\n

The solution is to adopt platforms that serve as this \u2018multi-tool,\u2019 providing integrated functions that manage, validate, and analyze data under one roof.<\/p>\n\n\n\n

A data product moves us past these obstacles to empower us to start using data to its full potential<\/strong><\/p>\n\n\n\n

Data product platforms are the ideal solution to these bottlenecks. They act as cohesive ecosystems, harmonizing fragmented data landscapes into unified, accessible, and actionable data repositories. By setting universal standards for data quality and validation, these platforms open-up opportunities for deeper insights, strong decision-making, and increased profitability and innovation. These data product platforms provide an in-depth look at the challenges of using data effectively while offering practical solutions and highlighting the high stakes involved in each barrier.<\/p>\n\n\n\n

By recognizing and addressing these barriers head-on, we become not only skilled data collectors but also equipped to turn this data into actionable intelligence. This fuels growth, drives innovation, and creates a business model that is not only sustainable but constantly evolving.<\/p>\n\n\n\n

About the Author<\/strong><\/p>\n\n\n

\n
\"\"<\/figure><\/div>\n\n\n

Sridhar Bankuru is the VP of Software Development at RightData<\/a>. Sridhar a brings broad range of implementation experience, managed complex client\u2019s distinctive set of challenges, solving strategic and operational issues especially in data integrations & data quality space. Before co-founding RightData, he has been part of many successful implementations playing architect \/ leadership roles, has experience as an accomplished data architect, hands-on as designer, and worked on performance.<\/em><\/p>\n\n\n\n

Sign up for the free insideBIGDATA newsletter<\/a>.<\/em><\/p>\n\n\n\n

Join us on Twitter: https:\/\/twitter.com\/InsideBigData1<\/a><\/em><\/p>\n\n\n\n

Join us on LinkedIn: https:\/\/www.linkedin.com\/company\/insidebigdata\/<\/a><\/em><\/p>\n\n\n\n

Join us on Facebook: https:\/\/www.facebook.com\/insideBIGDATANOW<\/a><\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

In this contributed article, Sridhar Bankuru, VP of Software Development at RightData, walks us through the top pain points of businesses today within their data trust journey, and looking ahead, how they can start trusting their data again.<\/p>\n","protected":false},"author":10531,"featured_media":33048,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"footnotes":""},"categories":[115,180,61,56,97,1],"tags":[280,237],"acf":[],"yoast_head":"\nThree Roadblocks to Using Data to Its Full Potential - insideBIGDATA<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/insidebigdata.com\/2023\/12\/02\/three-roadblocks-to-using-data-to-its-full-potential\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Three Roadblocks to Using Data to Its Full Potential - insideBIGDATA\" \/>\n<meta property=\"og:description\" content=\"In this contributed article, Sridhar Bankuru, VP of Software Development at RightData, walks us through the top pain points of businesses today within their data trust journey, and looking ahead, how they can start trusting their data again.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/insidebigdata.com\/2023\/12\/02\/three-roadblocks-to-using-data-to-its-full-potential\/\" \/>\n<meta property=\"og:site_name\" content=\"insideBIGDATA\" \/>\n<meta property=\"article:publisher\" content=\"http:\/\/www.facebook.com\/insidebigdata\" \/>\n<meta property=\"article:published_time\" content=\"2023-12-02T12:00:00+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-12-02T18:24:44+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/insidebigdata.com\/wp-content\/uploads\/2023\/08\/Data_center_shutterstock_1062915266_special.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1100\" \/>\n\t<meta property=\"og:image:height\" content=\"550\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Contributor\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@insideBigData\" \/>\n<meta name=\"twitter:site\" content=\"@insideBigData\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Contributor\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"4 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/insidebigdata.com\/2023\/12\/02\/three-roadblocks-to-using-data-to-its-full-potential\/\",\"url\":\"https:\/\/insidebigdata.com\/2023\/12\/02\/three-roadblocks-to-using-data-to-its-full-potential\/\",\"name\":\"Three Roadblocks to Using Data to Its Full Potential - insideBIGDATA\",\"isPartOf\":{\"@id\":\"https:\/\/insidebigdata.com\/#website\"},\"datePublished\":\"2023-12-02T12:00:00+00:00\",\"dateModified\":\"2023-12-02T18:24:44+00:00\",\"author\":{\"@id\":\"https:\/\/insidebigdata.com\/#\/schema\/person\/35a290930284d4cdbf002d457f3d5d87\"},\"breadcrumb\":{\"@id\":\"https:\/\/insidebigdata.com\/2023\/12\/02\/three-roadblocks-to-using-data-to-its-full-potential\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/insidebigdata.com\/2023\/12\/02\/three-roadblocks-to-using-data-to-its-full-potential\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/insidebigdata.com\/2023\/12\/02\/three-roadblocks-to-using-data-to-its-full-potential\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/insidebigdata.com\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Three Roadblocks to Using Data to Its Full Potential\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/insidebigdata.com\/#website\",\"url\":\"https:\/\/insidebigdata.com\/\",\"name\":\"insideBIGDATA\",\"description\":\"Your Source for AI, Data Science, Deep Learning & Machine Learning Strategies\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/insidebigdata.com\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"en-US\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/insidebigdata.com\/#\/schema\/person\/35a290930284d4cdbf002d457f3d5d87\",\"name\":\"Contributor\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/insidebigdata.com\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/secure.gravatar.com\/avatar\/36bffd267e38ed3f525205f67270e91b?s=96&d=mm&r=g\",\"contentUrl\":\"https:\/\/secure.gravatar.com\/avatar\/36bffd267e38ed3f525205f67270e91b?s=96&d=mm&r=g\",\"caption\":\"Contributor\"},\"url\":\"https:\/\/insidebigdata.com\/author\/contributor\/\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Three Roadblocks to Using Data to Its Full Potential - insideBIGDATA","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/insidebigdata.com\/2023\/12\/02\/three-roadblocks-to-using-data-to-its-full-potential\/","og_locale":"en_US","og_type":"article","og_title":"Three Roadblocks to Using Data to Its Full Potential - insideBIGDATA","og_description":"In this contributed article, Sridhar Bankuru, VP of Software Development at RightData, walks us through the top pain points of businesses today within their data trust journey, and looking ahead, how they can start trusting their data again.","og_url":"https:\/\/insidebigdata.com\/2023\/12\/02\/three-roadblocks-to-using-data-to-its-full-potential\/","og_site_name":"insideBIGDATA","article_publisher":"http:\/\/www.facebook.com\/insidebigdata","article_published_time":"2023-12-02T12:00:00+00:00","article_modified_time":"2023-12-02T18:24:44+00:00","og_image":[{"width":1100,"height":550,"url":"https:\/\/insidebigdata.com\/wp-content\/uploads\/2023\/08\/Data_center_shutterstock_1062915266_special.jpg","type":"image\/jpeg"}],"author":"Contributor","twitter_card":"summary_large_image","twitter_creator":"@insideBigData","twitter_site":"@insideBigData","twitter_misc":{"Written by":"Contributor","Est. reading time":"4 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/insidebigdata.com\/2023\/12\/02\/three-roadblocks-to-using-data-to-its-full-potential\/","url":"https:\/\/insidebigdata.com\/2023\/12\/02\/three-roadblocks-to-using-data-to-its-full-potential\/","name":"Three Roadblocks to Using Data to Its Full Potential - insideBIGDATA","isPartOf":{"@id":"https:\/\/insidebigdata.com\/#website"},"datePublished":"2023-12-02T12:00:00+00:00","dateModified":"2023-12-02T18:24:44+00:00","author":{"@id":"https:\/\/insidebigdata.com\/#\/schema\/person\/35a290930284d4cdbf002d457f3d5d87"},"breadcrumb":{"@id":"https:\/\/insidebigdata.com\/2023\/12\/02\/three-roadblocks-to-using-data-to-its-full-potential\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/insidebigdata.com\/2023\/12\/02\/three-roadblocks-to-using-data-to-its-full-potential\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/insidebigdata.com\/2023\/12\/02\/three-roadblocks-to-using-data-to-its-full-potential\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/insidebigdata.com\/"},{"@type":"ListItem","position":2,"name":"Three Roadblocks to Using Data to Its Full Potential"}]},{"@type":"WebSite","@id":"https:\/\/insidebigdata.com\/#website","url":"https:\/\/insidebigdata.com\/","name":"insideBIGDATA","description":"Your Source for AI, Data Science, Deep Learning & Machine Learning Strategies","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/insidebigdata.com\/?s={search_term_string}"},"query-input":"required name=search_term_string"}],"inLanguage":"en-US"},{"@type":"Person","@id":"https:\/\/insidebigdata.com\/#\/schema\/person\/35a290930284d4cdbf002d457f3d5d87","name":"Contributor","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/insidebigdata.com\/#\/schema\/person\/image\/","url":"https:\/\/secure.gravatar.com\/avatar\/36bffd267e38ed3f525205f67270e91b?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/36bffd267e38ed3f525205f67270e91b?s=96&d=mm&r=g","caption":"Contributor"},"url":"https:\/\/insidebigdata.com\/author\/contributor\/"}]}},"jetpack_featured_media_url":"https:\/\/insidebigdata.com\/wp-content\/uploads\/2023\/08\/Data_center_shutterstock_1062915266_special.jpg","jetpack_shortlink":"https:\/\/wp.me\/p9eA3j-8Ro","jetpack-related-posts":[{"id":16919,"url":"https:\/\/insidebigdata.com\/2017\/01\/14\/newvantage-partners-releases-5th-annual-big-data-executive-survey-for-2017\/","url_meta":{"origin":34062,"position":0},"title":"NewVantage Partners Releases 5th Annual Big Data Executive Survey for 2017","date":"January 14, 2017","format":false,"excerpt":"NewVantage Partners, strategic advisors in big data and business innovation to Fortune 1000 businesses, has released the results of its 2017 5th Annual Big Data Executive Survey, entitled \u201cBig Data Business Impact: Achieving Business Results through Innovation and Disruption.\u201d The 2017 Big Data Executive Survey reports what executives from 50\u2026","rel":"","context":"In "Big Data"","img":{"alt_text":"new-vantage-partners-2017-survey-infographic","src":"https:\/\/i0.wp.com\/insidebigdata.com\/wp-content\/uploads\/2017\/01\/New-Vantage-Partners-2017-Survey-Infographic.png?resize=350%2C200","width":350,"height":200},"classes":[]},{"id":25828,"url":"https:\/\/insidebigdata.com\/2021\/03\/27\/financial-chief-data-officers-making-advances-in-data-management-and-compliance-but-over-half-of-manual-processes-remain\/","url_meta":{"origin":34062,"position":1},"title":"Financial Chief Data Officers Making Advances in Data Management and Compliance but Over Half of Manual Processes Remain","date":"March 27, 2021","format":false,"excerpt":"A new survey, conducted by WBR Insights among data and information technology executives within the financial services sector and sponsored by InterSystems, highlights that financial organizations are allocating significant portions of their budget to compliance initiatives, and that 54% of those surveyed further revealed that at least half of these\u2026","rel":"","context":"In "Big Data"","img":{"alt_text":"","src":"https:\/\/i0.wp.com\/insidebigdata.com\/wp-content\/uploads\/2019\/10\/CDO_shutterstock_1023666928.jpg?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]},{"id":32879,"url":"https:\/\/insidebigdata.com\/2023\/07\/20\/power-to-the-data-report-podcast-large-language-models-for-executives\/","url_meta":{"origin":34062,"position":2},"title":"Power to the Data Report Podcast: Large Language Models for Executives","date":"July 20, 2023","format":false,"excerpt":"Hello, and welcome to the \u201cPower-to-the-Data Report\u201d\u00a0podcast\u00a0where we cover timely topics of the day from throughout the Big Data ecosystem. I am your host Daniel Gutierrez from insideBIGDATA where I serve as Editor-in-Chief & Resident Data Scientist. Today\u2019s topic is \u201cLarge Language Models for Executives.\u201d LLMs represent an important inflection\u2026","rel":"","context":"In "AI Deep Learning"","img":{"alt_text":"","src":"https:\/\/i0.wp.com\/insidebigdata.com\/wp-content\/uploads\/2023\/06\/Power-Data-column-banner_special.jpg?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]},{"id":12907,"url":"https:\/\/insidebigdata.com\/2015\/03\/22\/shift-happens-big-data-causing-a-fundamental-shift-in-c-suite-strategies\/","url_meta":{"origin":34062,"position":3},"title":"Shift Happens: Big Data Causing a Fundamental Shift in C-Suite Strategies","date":"March 22, 2015","format":false,"excerpt":"Platfora, the Big Data Analytics platform built natively on Apache Hadoop and Apache Spark, announced a study by The Economist Intelligence Unit (EIU) that explores, in detail, the beliefs, priorities and opinions on big data analytics by 395 C-level executives at Fortune 2000 companies.","rel":"","context":"In "Big Data"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":4343,"url":"https:\/\/insidebigdata.com\/2013\/10\/20\/big-data-survey-reports-steady-progress\/","url_meta":{"origin":34062,"position":4},"title":"Big Data Survey Reports Steady Progress","date":"October 20, 2013","format":false,"excerpt":"A recent survey of 500 U.S. business and IT executives\u00a0responsible for technical or strategic decisions affecting data at their company shows the big data phenomenon has business of all sizes re-evaluating methods and strategies for managing and using data. The survey was conducted by IT industry non-profit organization CompTIA. The\u2026","rel":"","context":"In "Analytics"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":11428,"url":"https:\/\/insidebigdata.com\/2014\/09\/17\/accenture-study-shows-satisfaction-business-outcomes-big-data\/","url_meta":{"origin":34062,"position":5},"title":"Accenture Study Shows Satisfaction with Business Outcomes from Big Data","date":"September 17, 2014","format":false,"excerpt":"Ninety-two percent of executives from companies that are applying big data to their businesses said they are satisfied with the results, according to new research by Accenture (NYSE: ACN).","rel":"","context":"In "Accenture"","img":{"alt_text":"","src":"https:\/\/i0.wp.com\/insidebigdata.com\/wp-content\/uploads\/2014\/04\/accenture-logo.jpg?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]}],"_links":{"self":[{"href":"https:\/\/insidebigdata.com\/wp-json\/wp\/v2\/posts\/34062"}],"collection":[{"href":"https:\/\/insidebigdata.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/insidebigdata.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/insidebigdata.com\/wp-json\/wp\/v2\/users\/10531"}],"replies":[{"embeddable":true,"href":"https:\/\/insidebigdata.com\/wp-json\/wp\/v2\/comments?post=34062"}],"version-history":[{"count":0,"href":"https:\/\/insidebigdata.com\/wp-json\/wp\/v2\/posts\/34062\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/insidebigdata.com\/wp-json\/wp\/v2\/media\/33048"}],"wp:attachment":[{"href":"https:\/\/insidebigdata.com\/wp-json\/wp\/v2\/media?parent=34062"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/insidebigdata.com\/wp-json\/wp\/v2\/categories?post=34062"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/insidebigdata.com\/wp-json\/wp\/v2\/tags?post=34062"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}