David Menninger's Analyst Perspectives
OCTOBER 7, 2020
For decades, data integration was a rigid process. Data was processed in batches once a month, once a week or once a day. Organizations needed to make sure those processes were completed successfully—and reliably—so they had the data necessary to make informed business decisions. The result was battle-tested integrations that could withstand the test of time.
Analytics Vidhya
OCTOBER 28, 2020
This article was published as a part of the Data Science Blogathon. Introduction The share price of HDFC Bank is going up. It’s on. The post Predicting Stock Prices using Reinforcement Learning (with Python Code!) appeared first on Analytics Vidhya.
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O'Reilly on Data
OCTOBER 22, 2020
“ On peut interroger n’importe qui, dans n’importe quel état; ce sont rarement les réponses qui apportent la vérité, mais l’enchaînement des questions. “ “ You can interrogate anyone, no matter what their state of being. It’s rarely their answers that unveil the truth, but the sequence of questions that you have to ask. “ – Inspector Pastor in La Fée Carabine, by Daniel Pennac.
datapine
OCTOBER 7, 2020
Using data in today’s businesses is crucial to evaluate success and gather insights needed for a sustainable company. Identifying what is working and what is not is one of the invaluable management practices that can decrease costs, determine the progress a business is making, and compare it to organizational goals. By establishing clear operational metrics and evaluate performance, companies have the advantage of using what is crucial to stay competitive in the market, and that’s data.
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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?
Rocket-Powered Data Science
OCTOBER 16, 2020
Artificial intelligence (AI) has become one of the most significant emerging technologies of the past few years. Some market estimates anticipate that AI will contribute 16 trillion dollars to the global GDP (gross domestic product) by 2030. While there has been accelerating interest in implementing AI as a technology, there has been concurrent growth in interest in implementing successful AI strategies.
BA Learnings
OCTOBER 4, 2020
Are you looking to create a business model canvas? As with most artefacts these days, you don’t need to start from scratch. There are a number of tools you can employ to brainstorm the details of your business model and present it in a professional format. The following tools have been provided as an initial starting point. Canvanizer Strategyzer Miro BMCanvas Conceptboard Vizzlo VisualParadigm CNVS Do you know of any other tools that should be on this list?
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
Analytics Vidhya
OCTOBER 14, 2020
Introduction In the recent years, face recognition applications have been developed on a much larger scale. Image classification and recognition has evolved and is. The post Building an end to end image classification/recognition application appeared first on Analytics Vidhya.
O'Reilly on Data
OCTOBER 13, 2020
The field of AI product management continues to gain momentum. As the AI product management role advances in maturity, more and more information and advice has become available. Our previous articles in this series introduce our own take on AI product management , discuss the skills that AI product managers need , and detail how to bring an AI product to market.
Paul Turley
OCTOBER 10, 2020
Moving important business data into a data model for analytic reporting can often be a two-edge sword. Data retrieval is fast and can support all kinds of analytic trending and comparisons. But, data in the model may be one or two layers away from the original source data, making it more challenging to compare with familiar user reports. Often the first validation effort after transforming and loading data into the model and then visualizing the initial results is having a business user say " ye
Domino Data Lab
OCTOBER 7, 2020
Guest Post by Bill Shannon, Founder and Managing Partner of BioRankings. Danger of Big Data. Big data is the rage. This could be lots of rows (samples) and few columns (variables) like credit card transaction data, or lots of columns (variables) and few rows (samples) like genomic sequencing in life sciences research. The Curse of Dimensionality , or Large P, Small N, ((P >> N)) , problem applies to the latter case of lots of variables measured on a relatively few number of sampl
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📌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.
erwin
OCTOBER 8, 2020
More and more companies are looking at cloud migration. Migrating legacy data to public, private or hybrid clouds provide creative and sustainable ways for organizations to increase their speed to insights for digital transformation, modernize and scale their processing and storage capabilities, better manage and reduce costs, encourage remote collaboration, and enhance security, support and disaster recovery.
David Menninger's Analyst Perspectives
OCTOBER 29, 2020
Every organization performing analytics with multiple employees needs to collaborate. They should be collaborating in the analytics process and in communicating the results of those analyses. As I continue my evaluation of analytics and data vendors , I have to admit some disappointment at the level of collaborative capabilities some analytics vendors provide.
Analytics Vidhya
OCTOBER 12, 2020
This article was published as a part of the Data Science Blogathon. Introduction I have always been in love with Data Visualization since the. The post Create a Word Cloud or Tag Cloud in Python appeared first on Analytics Vidhya.
Smart Data Collective
OCTOBER 25, 2020
The IoT is becoming increasingly commercialized. IDC estimates that there will be 41.6 billion IoT devices online by 2025. As the IoT continues to expand, companies across the world are looking for new ways to embrace its potential. One of the most overlooked benefits of the IoT is with indoor mapping. Companies can find a number of useful IoT approaches to achieve this goal.
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.
Paul Turley
OCTOBER 18, 2020
Moving important business data into a data model for analytic reporting can often be a two-edge sword. Data retrieval is fast and can support all kinds of analytic trending and comparisons. But, data in the model may be one or two layers away from the original source data, making it more challenging to compare with familiar user reports. Often the first validation effort after transforming and loading data into the model and then visualizing the initial results is having a business user say " ye
Jedox
OCTOBER 1, 2020
We have been talking about a digital transformation in Finance for ages. Some have come far on the journey while others are still struggling. Having just gone through a severe crisis that saw everyone working remotely and using digital tools makes this transformation more relevant than ever. . Right now, we are looking at two almost extreme cases: On one hand, we are at a stage where the transformation can be completed because of all the tools are available.
erwin
OCTOBER 16, 2020
It’s certainly no secret that data has been growing in volume, variety and velocity, and most companies are overwhelmed by managing it, let alone harnessing it to put it to work. We’re now generating 2.5 quintillion bytes of data every day, and 90% of the world’s data volume has been created in the past two years alone. With this absolute data explosion, it’s nearly impossible to filter out the time-sensitive data, the information that has immediate relevance and impact o
Martha Bennett
OCTOBER 28, 2020
In 2021, Forrester predicts 30% of blockchain projects will make it into production with the majority of those run on enterprise platforms. Find out more in our 2021 blockchain predictions.
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.
Analytics Vidhya
OCTOBER 5, 2020
This article was published as a part of the Data Science Blogathon. Overview Finishing in the top 10% in Machine Learning Hackathons is a. The post Ultimate Beginners Guide to Breaking into the Top 10% in Machine Learning Hackathons appeared first on Analytics Vidhya.
Smart Data Collective
OCTOBER 25, 2020
Machine learning has become a major game changer for the cryptocurrency industry. Most of the benefits are machine learning have been positive for the market. Machine learning is being used to predict price patterns more easily. However, some of these changes are not as welcome. Machine learning is making cryptocurrencies easier to trace. Since their inception, cryptocurrencies have gained popularity in several parts of the world.
Data Science 101
OCTOBER 24, 2020
This is a great talk for data scientists and managers of technology teams. If you do data science in 2020 or beyond, there is a good chance the cloud will be involved. Topics covered: Lessons learned when migrating data science (or technology in general) to the cloud AI services available via different cloud providers Workflows in the cloud and more.
Dataiku
OCTOBER 6, 2020
While a majority of AI’s business value comes from deploying models operationally, a significant percentage of data science projects never actually make it out of the lab to even start making a real-world impact. Why is that so? In this recap from a recent webinar with GigaOm Research featuring Dataiku’s Lead Data Scientist Katie Gross , we break down some of the key barriers to machine learning deployment and what data teams (notably data scientists) have the power to do to help prevent this fr
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.
erwin
OCTOBER 1, 2020
The erwin WFH (Work From Home) Impact Manager is a remote-work app that provides visibility and intelligence to help remote workers be more productive and process-compliant. The global pandemic is the single most disruptive event in modern times. Almost overnight organizations across the globe faced lockdowns, forcing them to switch to a remote-first workforce.
Cloudera
OCTOBER 1, 2020
Since 2013 the UK Government’s flagship ‘Cloud First’ policy has been at the forefront of enabling departments to shed their legacy IT architecture in order to meaningfully embrace digital transformation. The policy outlines that the cloud (and specifically, public cloud) be the default position for any new services; unless it can be demonstrated that other alternatives offer better value for money. .
Analytics Vidhya
OCTOBER 7, 2020
This article was published as a part of the Data Science Blogathon. Introduction Exploratory Data Analysis(EDA) is one of the most underrated and under-utilized. The post Exploratory Data Analysis – The Go-To Technique to Explore Your Data! appeared first on Analytics Vidhya.
Smart Data Collective
OCTOBER 11, 2020
Cloud design tools are creating a new future for the design profession. One study found that 47% of companies that use CAD software are implementing or strongly considering implementing a cloud-based CAD solution in the future. The number of professionals using other cloud-based design applications is even higher. We talked about the use of machine learning and big data in web development.
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.
Srividya Sridharan
OCTOBER 22, 2020
In 2021, business and IT leaders will be forced to tackle some long-lingering AI challenges head on to successfully emerge from the pandemic. Read Forrester's AI predictions to learn more.
Dataiku
OCTOBER 5, 2020
I had a great time earlier this week talking to the EGG audience at Dataiku about the past and future of algorithmic mistakes and harms. Broadly speaking, I introduced the concept of a “Weapon of Math Destruction” (WMD) as a predictive algorithm that is high stakes, opaque, and unfair. I gave examples from public education, hiring, the justice system, and credit.
erwin
OCTOBER 22, 2020
Thoughts on erwin Insights Day No. 2 Keynote. If you didn’t watch New York Times Best-Selling Author Keith Ferrazzi’s keynote from erwin Insights 2020 , what are you waiting for? I was blown away by Keith’s perspective on “Leading Without Authority” and it got me thinking about my own career, our employees here at erwin, work as we knew it, and work as we’ll know it in a post-COVID world.
Occam's Razor
OCTOBER 14, 2020
The gap between a bad and good data visualization is small. The gap between a good and great data visualization is a vast chasm! The challenge is that we, and our HiPPOs, bring opinions and feelings and our perceptions of what will go viral to the conversation. This is entirely counter productive to distinguishing between bad, good, and great. What we need instead is a rock solid understanding of the updraft we face in our quest for greatness, and a standard framework that can help us dispassion
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