Data Science Tech Brief By HackerNoon

Data Science Tech Brief By HackerNoon

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Data Science Tech Brief By HackerNoon episodes

  • The Top 16 Types of Charts in Data Visualization That You'll Use

    This story was originally published on HackerNoon at: https://hackernoon.com/top-16-types-of-chart-in-data-visualization-hrh32wv.


    In the era of information explosion, more and more data piles up. However, these dense data are unfocused and less readable. So we need data visualization to help data to be easily understood and accepted. By contrast, visualization is more intuitive and meaningful, and it is very important to use appropriate charts to visualize data.
    Check more stories related to data-science at: https://hackernoon.com/c/data-science.
    You can also check exclusive content about #data-visualization, #big-data, #latest-tech-stories, #hackernoon-top-story, #data-representation, #how-to-visualize-data, #column-chart-vs-bar-chart, #area-chart-vs-pie-chart, #hackernoon-es, and more.


    This story was written by: @sage. Learn more about this writer by checking @sage's about page,
    and for more stories, please visit hackernoon.com.


    The Top 16 Types of Charts in Data Visualization That You'll Use: Column Chart, Bar Chart, Scatter Plot, Bubble Chart, Radar Chart and Bubble Chart. All the charts in the article are taken from the data visualization tool FineReport. The chart is used to show the change of data over a continuous time interval or time span. It is characterized by a tendency to reflect things as they change over time or ordered categories. It should be noted that the number of data records of the line graph should be greater than 2.

    10 min
  • Data in AI: A Deep Dive With Jerome Pasquero

    This story was originally published on HackerNoon at: https://hackernoon.com/data-in-ai-a-deep-dive-with-jerome-pasquero.


    How is Data Transforming AI - The What's AI Podcast (episode 27)
    Check more stories related to data-science at: https://hackernoon.com/c/data-science.
    You can also check exclusive content about #data, #big-data, #data-security, #ai, #artificial-intelligence, #machine-learning, #jerome-pasquero, #what's-ai, and more.


    This story was written by: @whatsai. Learn more about this writer by checking @whatsai's about page,
    and for more stories, please visit hackernoon.com.


    This week's episode of the What's AI podcast features Machine Learning Director Jerome Pasquero. We discussed the role of human judgment in data annotation. We also touched on the often subtle yet significant presence of AI in our daily routines. This episode is a must for anyone curious about the ways in which data fuels AI.

    3 min
  • 14 Best Tableau Datasets for Practicing Data Visualization

    This story was originally published on HackerNoon at: https://hackernoon.com/14-best-tableau-datasets-for-practicing-data-visualization.


    This article focuses on the 14 Best Tableau Datasets for Practicing Data Visualization, which is essential for business analysts and data scientists.
    Check more stories related to data-science at: https://hackernoon.com/c/data-science.
    You can also check exclusive content about #tableau, #data, #datasets, #covid-19-datasets, #data-visualization, #data-visualization-tools, #data-analysis, #tableau-vs-powerbi, and more.


    This story was written by: @datasets. Learn more about this writer by checking @datasets's about page,
    and for more stories, please visit hackernoon.com.


    Tableau is a data analysis and visualization tool that enables users to connect, visualize and share data in an easy-to-understand and meaningful way. This article focuses on the 14 Best Tableau Datasets for Practicing Data Visualization, essential for helping you gain valuable experience.

    19 min
  • The Lifecycle of a Data Warehouse

    This story was originally published on HackerNoon at: https://hackernoon.com/the-lifecycle-of-a-data-warehouse.


    We're about to embark on the fascinating journey of building a data warehouse, guided by our adept Data Architect.
    Check more stories related to data-science at: https://hackernoon.com/c/data-science.
    You can also check exclusive content about #data-warehouse, #business-intelligence, #databases, #cloud-storage, #etl, #olap, #database-management, #relational-database, and more.


    This story was written by: @ishaanraj. Learn more about this writer by checking @ishaanraj's about page,
    and for more stories, please visit hackernoon.com.


    A data warehouse, optimized for OLAP (Online Analytical Processing), is a centralized repository for structured and processed data.
    Unlike traditional OLTP (Online Transaction Processing) systems, it's designed for efficient querying and reporting. The use of columnar storage in data warehouses allows for quicker data retrieval, especially beneficial for analytical queries.

    9 min
  • Advancing Data Quality: Exploring Data Contracts with Lyft

    This story was originally published on HackerNoon at: https://hackernoon.com/advancing-data-quality-exploring-data-contracts-with-lyft.


    Keen to delve into data contracts and discover how they can enhance your data quality? Join me as we explore Lyft's Verity data contract approach together!
    Check more stories related to data-science at: https://hackernoon.com/c/data-science.
    You can also check exclusive content about #data-quality, #data-rel, #data-engineering, #data, #lyf, #data-observability, #verity-review, #hackernoon-top-story, #hackernoon-es, #hackernoon-hi, #hackernoon-zh, #hackernoon-fr, #hackernoon-bn, #hackernoon-ru, #hackernoon-vi, #hackernoon-pt, #hackernoon-ja, #hackernoon-de, #hackernoon-ko, #hackernoon-tr, and more.


    This story was written by: @bmarquie. Learn more about this writer by checking @bmarquie's about page,
    and for more stories, please visit hackernoon.com.


    In a previous post, I explored Airbnb’s strategy for enhancing data quality through incentives. Lyft is taking a distinct approach, not attempting the same thing differently, but rather focusing on different aspects of data quality. Lyft places emphasis on actively testing and validating data quality, providing both producers and consumers with the means to effectively improve and control the quality.

    16 min
  • Building a CI Pipeline with Databricks dbx Tool and GitLab

    This story was originally published on HackerNoon at: https://hackernoon.com/building-a-ci-pipeline-with-databricks-dbx-tool-and-gitlab.


    Explore streamlined CI/CD in Databricks with Asset Bundles. Simplify deployment, eliminate complexities, and enhance workflow efficiency
    Check more stories related to data-science at: https://hackernoon.com/c/data-science.
    You can also check exclusive content about #databricks, #mlops, #ci-cd-pipelines, #gitlab-ci, #devops, #dbx, #databricks-assets, #devops-guide, and more.


    This story was written by: @neshom. Learn more about this writer by checking @neshom's about page,
    and for more stories, please visit hackernoon.com.


    discover how to implement a robust CI/CD pipeline using Databricks DBX and GitLab. Tailored for data engineering and science, this guide unravels CI/CD fundamentals, Databricks integration, and the pivotal role of Databricks CLI Extension (DBX). The hands-on example showcases the seamless deployment of a Databricks workflow, automating data manipulation, analysis, and testing. As we bridge CI/CD principles with Databricks workflows, you'll gain practical insights into enhancing data project efficiency and reliability. This blog serves as a comprehensive resource for those seeking to optimize their data processing workflows through the integration of cutting-edge CI/CD practices with Databricks capabilities.

    13 min
  • Meeting Customer Needs With User-Centric Product Development

    This story was originally published on HackerNoon at: https://hackernoon.com/meeting-customer-needs-with-user-centric-product-development.


    In a nutshell, user-centric product development implies attentiveness to the client's needs. This approach puts the customer at the heart of the product
    Check more stories related to data-science at: https://hackernoon.com/c/data-science.
    You can also check exclusive content about #customer-experience, #user-centric-designing, #product-development, #product-design, #product-management, #user-centric-design, #customer-engagement, #customer-needs, and more.


    This story was written by: @tonythevoit. Learn more about this writer by checking @tonythevoit's about page,
    and for more stories, please visit hackernoon.com.


    Today, it has become difficult to compete with other solutions on the market if your product or service does not meet the user's expectations. Markets have become more saturated, and users now lean toward products that solve their problems and that are friendly and easy to navigate.
    Businesses that have adopted a user-centric approach are finding greater success through increased customer satisfaction and loyalty. Importantly, users who feel valued and heard are more likely to become loyal to the product and actively promote it.

    9 min
  • Is Your Data Worth the Costs?

    This story was originally published on HackerNoon at: https://hackernoon.com/is-your-data-worth-the-costs.


    Data, when used strategically, can be a powerful tool for businesses to achieve their goals.
    Check more stories related to data-science at: https://hackernoon.com/c/data-science.
    You can also check exclusive content about #data, #data-driven, #data-hoarding, #kpis, #data-strategy, #data-governance, #user-experience, #what-is-product-value, and more.


    This story was written by: @liorb. Learn more about this writer by checking @liorb's about page,
    and for more stories, please visit hackernoon.com.


    Data, when used strategically, can be a powerful tool for businesses to achieve their goals. However, it is important to approach data with a clear plan and to avoid the hidden costs of data hoarding. By prioritizing relevant data, evaluating its impact on business outcomes, and continuously refining data-driven strategies, businesses can unlock the true potential of data to drive growth, improve efficiency, and achieve sustainable success.

    21 min
  • How to Modify the Number of Rows Fetched by SAP BusinessObjects Report

    This story was originally published on HackerNoon at: https://hackernoon.com/how-to-modify-the-number-of-rows-fetched-by-sap-businessobjects-report.


    If your BO Report exceeds the 5000 rows, you may miss out on critical data or insights.
    Check more stories related to data-science at: https://hackernoon.com/c/data-science.
    You can also check exclusive content about #business-intelligence, #sap-erp, #data-analysis, #data-analytics, #data-analyst, #sap-businessobjects-report, #rows-fetched-in-sap, #sap-business-objects, and more.


    This story was written by: @luca1iu. Learn more about this writer by checking @luca1iu's about page,
    and for more stories, please visit hackernoon.com.


    If your BO Report exceeds the 5000 rows, you may miss out on critical data or insights.

    2 min
  • How to Fetch SAP Business Objects Universes Using Python

    This story was originally published on HackerNoon at: https://hackernoon.com/how-to-fetch-sap-business-objects-universes-using-python.


    With the RESTful API, developers can perform operations like fetching information about reports, universes, folders, scheduling, and other BI-related entities.
    Check more stories related to data-science at: https://hackernoon.com/c/data-science.
    You can also check exclusive content about #business-intelligence, #data-analyst, #python, #rest-api, #sap, #sap-business-objects, #data-analysis, #businessobjects-restful, and more.


    This story was written by: @luca1iu. Learn more about this writer by checking @luca1iu's about page,
    and for more stories, please visit hackernoon.com.


    With the RESTful API, developers can perform operations like fetching information about reports, universes, folders, scheduling, and other BI-related entities.

    3 min

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