August, 2022

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Metaverse: The time for CIOs to experiment is now

CIO Business Intelligence

For the past forty years CIOs have labored to retrofit, rearchitect, and ultimately replace underfunded and underappreciated legacy infrastructures in hopes of delivering the full benefits associated with periodically occurring waves of transformative emerging technologies. Debate now rages in IT and digital communities regarding what will be the seismic technological shift of the 2020s.

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Qlik Advances Self-Service Analytics and Business Intelligence

David Menninger's Analyst Perspectives

The analytics and business intelligence market landscape continues to grow as more organizations seek robust tools and capabilities to visualize and better understand data. BI systems are used to perform data analysis, identify market trends and opportunities and streamline business processes. They can collect and combine data from internal and external systems to present a holistic view.

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On Technique

O'Reilly on Data

In a previous article , I wrote about how models like DALL-E and Imagen disassociate ideas from technique. In the past, if you had a good idea in any field, you could only realize that idea if you had the craftsmanship and technique to back it up. With DALL-E, that’s no longer true. You can say, “Make me a picture of a lion attacking a horse,” and it will happily generate one.

Software 267
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Building a simple Flask App using Docker vs Code

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction More often than not, developers run into issues of an application running on one machine versus not running on another. Dockers help prevent this by ensuring the application runs on any machine if it works on yours. Simply put, if your job as […]. The post Building a simple Flask App using Docker vs Code appeared first on Analytics Vidhya.

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15 Modern Use Cases for Enterprise Business Intelligence

Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

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7 Techniques to Handle Imbalanced Data

KDnuggets

This blog post introduces seven techniques that are commonly applied in domains like intrusion detection or real-time bidding, because the datasets are often extremely imbalanced.

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7 Enterprise Applications for Companies Using Cloud Technology

Smart Data Collective

The market for cloud technology is booming. Companies spent over $405 billion on cloud services last year. The sudden growth is not surprising, because the benefits of the cloud are incredible. Enterprise cloud technology applications are the future industry standard for corporations. Cloud computing has found its way into many business scenarios and is a relatively new concept for businesses.

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AI for Time Travel? Well, Almost

Dataiku

AI predictions compress time: Reduce credit card refunds from 60 to 30 days or time to detect chip manufacturing problems from 36 hours to zero. Increasingly, companies are going beyond zero and using AI to detect things before they happen: identifying the purchase of a large screen TV with a stolen credit card hours before it happens, replacing an airplane valve days before it fails, and flagging semiconductor manufacturing defects an hour before they’re produced.

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Scaling False Peaks

O'Reilly on Data

Humans are notoriously poor at judging distances. There’s a tendency to underestimate, whether it’s the distance along a straight road with a clear run to the horizon or the distance across a valley. When ascending toward a summit, estimation is further confounded by false summits. What you thought was your goal and end point turns out to be a lower peak or simply a contour that, from lower down, looked like a peak.

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Introduction to Requests Library in Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Requests in Python is a module that can be used to send all kinds of HTTP requests. It is straightforward to use and is a human-friendly HTTP Library. Using the requests library; we do not need to manually add the query string […]. The post Introduction to Requests Library in Python appeared first on Analytics Vidhya.

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What Does ETL Have to Do with Machine Learning?

KDnuggets

ETL during the process of producing effective machine learning algorithms is found at the base - the foundation. Let’s go through the steps on how ETL is important to machine learning.

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8 Steps to Transformation at Speed & Scale – Your Guide to Deploying StratOps

📌Is your Data & AI transformation struggling to really impact the business? Discover the game-changing StratOps approach that: Bridges the Gap : Connect your Data & AI strategy to your operating model, to ensure alignment at every level. Prioritizes Outcomes : Focuses on concrete business outcomes from day one, rather than capabilities in isolation.

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SQL Server and the Cast Function for Data-Driven Companies

Smart Data Collective

A growing number of businesses are relying on big data technology to improve productivity and address some of their most pressing challenges. Global companies are projected to spend over $297 billion on big data by 2030. Data technology has proven to be remarkably helpful for many businesses. However, companies also encounter a number of challenges as they try to leverage the benefits of big data.

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Digital twins are primed to revolutionize the infrastructure industry

CIO Business Intelligence

Elaborating on some points from my previous post on building innovation ecosystems, here’s a look at how digital twins , which serve as a bridge between the physical and digital domains, rely on historical and real-time data, as well as machine learning models, to provide a virtual representation of physical objects, processes, and systems. Keith Bentley of software developer Bentley Systems describes digital twins as the biggest opportunity for IT value contribution to the physical infrastructu

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Incremental Strategies to Move Your Data Strategy Forward Remove Obstacles to Unlock Possibilities in Financial Services

Cloudera

Firms are burdened with tech debt and endless regulatory compliance, often leaving innovation last to receive the necessary budgets. Data-fuelled innovation requires a pragmatic strategy. This blog lays out some steps to help you incrementally advance efforts to be a more data-driven, customer-centric organization. Embrace incremental progress. The financial sector’s evolution is unleashing myriad demands on firms operating in the market.

Strategy 106
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What Can WordleBot Teach Us About Actionable Data Insights?

Juice Analytics

I’m a Wordle obsessive. Which is to say, every morning I find myself staring deep into my coffee in search of an elusive 5-letter word. The New York Times (who bought the word game from software developer Josh Wardle for $3 million) knows their audience. We may be playing with words, but the analytical nature of this game is the appeal. It is a game of odds and mathematical deduction as we try to reduce the potential options available.

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Marketing Operations in 2025: A New Framework for Success

Speaker: Mike Rizzo, Founder & CEO, MarketingOps.com and Darrell Alfonso, Director of Marketing Strategy and Operations, Indeed.com

Though rarely in the spotlight, marketing operations are the backbone of the efficiency, scalability, and alignment that define top-performing marketing teams. In this exclusive webinar led by industry visionaries Mike Rizzo and Darrell Alfonso, we’re giving marketing operations the recognition they deserve! We will dive into the 7 P Model —a powerful framework designed to assess and optimize your marketing operations function.

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The Ultimate Guide To Pandas For Data Science!

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction 2.5 quintillion bytes of data are produced every day! Consider how much we can deduce from that and what conclusions we can draw. Wait! But, how do we deal with such a massive amount of data? Not to worry; the Pandas library […]. The post The Ultimate Guide To Pandas For Data Science!

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The Importance of Experiment Design in Data Science

KDnuggets

Do you feel overwhelmed by the sheer number of ideas that you could try while building a machine learning pipeline? You can not take the liberty of trying all possible ways to arrive at a solution - hence we discuss the importance of experiment design in data science projects.

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5 Ways B2B Companies Can Use Analytics for Pricing

Smart Data Collective

Analytics technology is very important for modern business. Companies spent over $240 billion on big data analytics last year. That figure is expected to grow as more businesses discover its benefits. There are many important applications of data analytics technology. One of the most important is with helping companies set their prices correctly. Analytics Can Be Essential for Helping Companies with their Pricing Strategies.

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What is data visualization? Presenting data for decision-making

CIO Business Intelligence

Data visualization definition. Data visualization is the presentation of data in a graphical format such as a plot, graph, or map to make it easier for decision makers to see and understand trends, outliers, and patterns in data. Maps and charts were among the earliest forms of data visualization. One of the most well-known early examples of data visualization was a flow map created by French civil engineer Charles Joseph Minard in 1869 to help understand what Napoleon’s troops suffered in the d

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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin

As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.

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Speeding up Queries With Z-Order

Cloudera

Z-order is an ordering for multi-dimensional data, e.g. rows in a database table. Once data is in Z-order it is possible to efficiently search against more columns. This article reveals how Z-ordering works and how one can use it with Apache Impala. In a previous blog post , we demonstrated the power of Parquet page indexes, which can greatly improve the performance of selective queries.

IoT 106
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Text AI Updates Drive Faster Business Value

DataRobot Blog

How can you save time in understanding the impact of language when working with text in ML models ? With tens of thousands of Text AI projects, DataRobot has helped organizations unlock insights from text and generate predictions with text models—from assisting with customer support ticket triage to predicting real estate sale prices. Continuing to build on previously released Text AI capabilities, DataRobot AI Cloud introduces new features to help with language detection, blueprint optimization

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Multi-variate Time Series Forecasting using Kats Model

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Kats model-which is also developed by Facebook Research Team-supports the functionality of multi-variate time-series forecasting in addition to univariate time-series forecasting. Often we need to forecast a time series where we have input variables in addition to ‘time’; this is where the […].

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How Do Data Scientists and Data Engineers Work Together?

KDnuggets

If you’re considering a career in data science, it’s important to understand how these two fields differ, and which one might be more appropriate for someone with your skills and interests.

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The Ultimate Guide To Data-Driven Construction: Optimize Projects, Reduce Risks, & Boost Innovation

Speaker: Donna Laquidara-Carr, PhD, LEED AP, Industry Insights Research Director at Dodge Construction Network

In today’s construction market, owners, construction managers, and contractors must navigate increasing challenges, from cost management to project delays. Fortunately, digital tools now offer valuable insights to help mitigate these risks. However, the sheer volume of tools and the complexity of leveraging their data effectively can be daunting. That’s where data-driven construction comes in.

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Data-Driven Employee Reviews Are Less Biased and Unfair

Smart Data Collective

Data analytics technology has changed many aspects of the modern workplace. A growing number of companies are using data to make more informed hiring decisions , track payroll issues and resolve internal problems. One of the most important benefits of data analytics is that it can help companies monitor employee performance and provide more accurate feedback.

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The Right Stuff: The Role of MLOps in AI Success

CIO Business Intelligence

Great teams incorporate a variety of skill sets. For example, a football team consisting of 11 quarterbacks would get crushed in a game against talented linemen, running backs and receivers. It’s no different when building a team for an enterprise AI project; you can’t just throw a bunch of data scientists into a room and expect them to come up with a revenue-generating or efficiency-improving project without support from other members of the enterprise.

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15 Lessons from the Data Story Creative Process

Juice Analytics

What do you get when you put a Data Scientist and a Data Storyteller in a room full of executives for two days? Sorry, no punchline…this is serious. The answer is The Data Story Creative Process (DSCP) workshop — a hands-on, case study-based learning event that teaches a framework for using data to drive informed action. We played with data, explored insights, structured stories, and discussed the barriers to reaching our audience.

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Visualizing 24 School Divisions’ Submissions with a Dashboard in Microsoft Excel

Depict Data Studio

This guest post comes from Amadu Sidi Bah, who’s graduated from our Simple Spreadsheets, Great Graphs, Report Redesign, and Dashboard Design courses. Great work, Amadu! — Ann K. Emery. All too often, written submissions from stakeholders come in dense, long reports. That’s what happened in our project when stakeholders were consulted on the changes that would be required to improve student outcomes.

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Launching LLM-Based Products: From Concept to Cash in 90 Days

Speaker: Christophe Louvion, Chief Product & Technology Officer of NRC Health and Tony Karrer, CTO at Aggregage

Christophe Louvion, Chief Product & Technology Officer of NRC Health, is here to take us through how he guided his company's recent experience of getting from concept to launch and sales of products within 90 days. In this exclusive webinar, Christophe will cover key aspects of his journey, including: LLM Development & Quick Wins 🤖 Understand how LLMs differ from traditional software, identifying opportunities for rapid development and deployment.

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12 FAQs on AWS Asked in Interviews

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction The way big business tycoons run has changed a lot since the past. The concept of “Cloud Computing” has played a major role in this. This implementation of cloud computing technology has led to the need for Cloud Computing Experts. The software team […].

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Data Transformation: Standardization vs Normalization

KDnuggets

Increasing accuracy in your models is often obtained through the first steps of data transformations. This guide explains the difference between the key feature scaling methods of standardization and normalization, and demonstrates when and how to apply each approach.

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The Future of AI: High Quality, Human Powered Data

Smart Data Collective

Artificial Intelligence (AI) has significantly altered how work is done. However, AI even has a bigger impact by enhancing human capabilities. Research conducted by the Harvard Business Review found that the interaction between machines and humans significantly improves firms’ performance. Successful collaboration between humans and machines enhances each other’s strengths, including teamwork, leadership, creativity, speed, scalability, and quantitative capabilities.

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The rise of the data lakehouse: A new era of data value

CIO Business Intelligence

With 65 million vaccine doses to administer at the height of the COVID-19 pandemic, Luigi Guadagno, CIO of Walgreens, needed to know where to send them. To find out, he queried Walgreens’ data lakehouse, implemented with Databricks technology on Microsoft Azure. “We leveraged the lakehouse to understand the moment,” the CIO says. For Guadagno, the need to match vaccine availability with patient demand came at the right moment, technologically speaking.

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Enhance Customer Value: Unleash Your Data’s Potential

The complexity of financial data, the need for real-time insight, and the demand for user-friendly visualizations can seem daunting when it comes to analytics - but there is an easier way. With Logi Symphony, we aim to turn these challenges into opportunities. Our platform empowers you to seamlessly integrate advanced data analytics, generative AI, data visualization, and pixel-perfect reporting into your applications, transforming raw data into actionable insights.