Sat.Aug 07, 2021 - Fri.Aug 13, 2021

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Top 7 business intelligence trends for 2021

CIO Business Intelligence

Business intelligence is not an oxymoron like jumbo shrimp. It’s not dead. And it’s not being superseded by artificial intelligence.

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Explore the Magic Methods in Python

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Magic Methods Magic methods are special methods in python that have. The post Explore the Magic Methods in Python appeared first on Analytics Vidhya.

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Accelerating Drug Discovery and Development with DataOps

DataKitchen

A drug company tests 50,000 molecules and spends a billion dollars or more to find a single safe and effective medicine that addresses a substantial market. Figure 1 shows the 15-year cycle from screening to government agency approval and phase IV trials. Drug companies desperately look for ways to compress this lengthy time frame and to demonstrate the competitive advantage of their intellectual property.

Testing 246
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Increase Analytics Influence: Leverage Predictive Metrics!

Occam's Razor

Almost all metrics you currently use have one common thread: They are almost all backward-looking. If you want to deepen the influence of data in your organization – and your personal influence – 30% of your analytics efforts should be centered around the use of forward-looking metrics. Predictive metrics! But first, let's take a small step back.

Metrics 143
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Optimizing The Modern Developer Experience with Coder

Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.

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7 Ways to Improve Your Client Reporting

Juice Analytics

Presenting data to customers or clients is an opportunity: it is a chance to shape how they look at your solution, demonstrate the value you deliver, and guide them to better decisions. Unfortunately, a lot of client reporting is treated as a check-the-box activity. We wanted to share some examples of high impact reporting and the features that make them effective: 1.

Reporting 140
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Multivariate Time Series Anomaly Detection using VAR model

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon What is Anomaly Detection? Anomaly detection detects anomalies in the data. The post Multivariate Time Series Anomaly Detection using VAR model appeared first on Analytics Vidhya.

Modeling 399

More Trending

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Businesses Across Various Industry Verticals Use Data Analytics

Smart Data Collective

Big data and analytics technology is rapidly changing the future of modern business. Over 67% of companies spend over $10,000 a year on analytics solutions. Investments in analytics are being made across all major industries. ‘Although companies in healthcare, IT and finance are some of the biggest investors in analytics technology, plenty of other sectors are investing in analytics as well.

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3 Reasons Why Most Digital Transformation Initiatives Continue To Fail

BA Learnings

Are you thinking about initiating a digital transformation campaign in your company? If so, you may be worried about what could go wrong, and the challenges that possibly lie ahead. You’ve probably heard about the many unsuccessful stories, and you’re right to be concerned. Boston Consulting Group conducted a digital transformation study in 2020 to find out why such projects are missing the mark.

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Mathematical Modelling: Modelling the Spread of Diseases with SIRD Model

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction According to Haines and Crounch, mathematical modelling is a process. The post Mathematical Modelling: Modelling the Spread of Diseases with SIRD Model appeared first on Analytics Vidhya.

Modeling 398
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DBTA Readers’ Choice Awards, 2021

DataKitchen

The post DBTA Readers’ Choice Awards, 2021 first appeared on DataKitchen.

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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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Importance of Data-Driven Cybersecurity for Medical Device Companies

Smart Data Collective

Big data has become fundamentally important to the future of cybersecurity. A growing number of companies using data analytics, artificial intelligence and other forms of big data technology to bolster their defenses against cyberattacks. Medical device companies are highly vulnerable to cyberattacks. A growing number of these businesses are investing in big data technology to help keep hackers at bay.

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Data Exploration with Pandas Profiler and D-Tale

Domino Data Lab

We all have heard how data is the new oil. I always say that if that is the case, we need to go through some refinement process before that raw oil is converted into useful products. For data, this refinement includes doing some cleaning and manipulations that provide a better understanding of the information that we are dealing with. In a previous blog , we have covered how Pandas Profiling can supercharge the data exploration required to bring our data into a predictive modelling phase.

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Slack Data Engineering: Design and Architecture

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Ref :[link] Introduction: Slack is a communication platform. Users send. The post Slack Data Engineering: Design and Architecture appeared first on Analytics Vidhya.

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Five Reasons Why Platforms Beat Point Solutions in Every Business Case

Cloudera

Once upon an IT time, everything was a “point product,” a specific application designed to do a single job inside a desktop PC, server, storage array, network, or mobile device. Point solutions are still used every day in many enterprise systems, but as IT continues to evolve, the platform approach beats point solutions in almost every use case.

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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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5 Analytic Tools Companies Use To Organize and Study their Data

Smart Data Collective

In today’s market, it’s hard to thrive or even just survive without collecting data. Companies have to understand their customers better than they do, study their competitors and understand how cultural and global influences affect their positioning. Data can help them create strategies based on these powerful forces. The good news is that it’s never been easier to collect and organize data.

Analytics 132
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The Value of Explainable AI

Dataiku

Explainable AI has become a powerful mitigating force that enables modelers, regulators, and laypeople to have more trust and confidence in machine learning models. However, it’s not always easy for data scientists to implement models that are explainable. To help them do so in practice — and raise awareness for some of the pitfalls they may encounter — we held a webinar on the topic that focused on the tradeoffs between white-box and black-box models, fairness and explainability concepts both b

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Email Spam Detection – A Comparative Analysis of 4 Machine Learning Models

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction This article aims to compare four different deep learning and. The post Email Spam Detection – A Comparative Analysis of 4 Machine Learning Models appeared first on Analytics Vidhya.

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Why Modernizing the First Mile of the Data Pipeline Can Accelerate all Analytics

Cloudera

Every enterprise is trying to collect and analyze data to get better insights into their business. Whether it is consuming log files, sensor metrics, and other unstructured data, most enterprises manage and deliver data to the data lake and leverage various applications like ETL tools, search engines, and databases for analysis. This whole architecture made a lot of sense when there was a consistent and predictable flow of data to process.

Analytics 111
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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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Demand for Data-Savvy Cybersecurity Professionals Grows In 2021

Smart Data Collective

Big data is becoming increasingly important in the cybersecurity profession. A number of IT security professionals are using big data and AI technology to create more robust cybersecurity solutions. As cybersecurity threats become more serious, the demand for data-savvy cybersecurity experts will continue to rise. This figure has already surged in 2021.

Big Data 131
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Dataiku + Your Favorite BI Tool: How to (and Why) Integrate

Dataiku

Dataiku’s end-to-end platform gives our users the ability to turn raw data into business-impacting decisions using advanced predictive analytics. In addition, Dataiku serves a large variety of user personas, technical skills, industries, and use cases. In this blog post, we're going to show you how you can expand Dataiku’s value within your organizations even further by integrating with your BI tool of choice to uplevel from prescriptive to predictive analyses.

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Twitter-based Gender Classification -A Machine Learning Project

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction- With the rise of social media in recent years, there. The post Twitter-based Gender Classification -A Machine Learning Project appeared first on Analytics Vidhya.

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The Foundations of a Modern Data-Driven Organisation: Change from Within (part 2 of 2)

Cloudera

In my previous blog post, I shared examples of how data provides the foundation for a modern organization to understand and exceed customers’ expectations. However, the important role data occupies extends beyond customer experience and revenue, as it becomes increasingly central in optimizing internal processes for the long-term growth of an organization.

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The Cloud Development Environment Adoption Report

Cloud Development Environments (CDEs) are changing how software teams work by moving development to the cloud. Our Cloud Development Environment Adoption Report gathers insights from 223 developers and business leaders, uncovering key trends in CDE adoption. With 66% of large organizations already using CDEs, these platforms are quickly becoming essential to modern development practices.

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8 Modeling Tools to Build Complex Algorithms

Domino Data Lab

For a model-driven enterprise, having access to the appropriate tools can mean the difference between operating at a loss with a string of late projects lingering ahead of you or exceeding productivity and profitability forecasts. This is no exaggeration by any means. With the right tools, your data science teams can focus on what they do best – testing, developing and deploying new models while driving forward-thinking innovation.

Modeling 111
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Addressing CRM Data Quality with Dataiku

Dataiku

Using machine learning (ML) to predict customer growth, churn, and to find insights in the data is not only a trendy topic, but also something that can bring a lot of value. However, there is an essential prerequisite for any machine learning model, and machine learning models for these use cases are no different: good-quality data (in this case customer relationship management or CRM data).

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Implementing Convolution As An Image Filter Using OpenCV

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction to Convolution Convolution is a trendy term in computer vision. The post Implementing Convolution As An Image Filter Using OpenCV appeared first on Analytics Vidhya.

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Generating and Viewing Lineage through Apache Ozone

Cloudera

Follow your data in object storage on-premises. As businesses look to scale-out storage, they need a storage layer that is performant, reliable and scalable. With Apache Ozone on the Cloudera Data Platform (CDP) , they can implement a scale-out model and build out their next generation storage architecture without sacrificing security, governance and lineage.

Testing 106
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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

Speaker: Jay Allardyce, Deepak Vittal, Terrence Sheflin, and Mahyar Ghasemali

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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Beer Industry Buzz: How Data Helps Buyers Find Their Next Brew

Sisense

Blog. Do we live in a golden age of beer? Indications show that this centuries-old beverage of choice is having a modern renaissance, in terms of both quality and variety. Beer culture has risen in the US and worldwide, with over a half-trillion USD in sales annually ?— and so has worldwide innovation within and outside the industry. Options have exploded in recent years.

Sales 98
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The Journey to an Enterprise Data Mesh

Dataiku

Everywhere one looks in the data blogs these days, people are expounding the freedom and scalability of a data mesh, but very little is being said about how one actually builds towards having this mystical mesh. While a microservices pattern aims to expose software as a network of discoverable, secure, and scalable atomic services, a data mesh conceives of data access and data services like inference engines as a similar set of composable data services.

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Implementing Artificial Neural Network on Unstructured Data

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon In the last blog, we discussed what an Artificial Neural network. The post Implementing Artificial Neural Network on Unstructured Data appeared first on Analytics Vidhya.

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How Knowledge Graphs Can Help Large Healthcare Institutions Track the Impact of Faculty Research

Ontotext

One of our clients is a major children’s hospital in the Midwestern United States. Apart from being a large medical service provider, the institution is also a major research center with several hundred faculty members engaged in a variety of scientific activities beyond their medical duties. Between them, the faculty members have published more than ten thousand peer-reviewed scientific articles, many in top ranking Pediatrics journals.

Metrics 98
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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.