Analytics Vidhya
JANUARY 15, 2022
This article was published as a part of the Data Science Blogathon. Overview The core of the data science project is data & using it to build predictive models and everyone is excited and focused on building an ML model that would give us a near-perfect result mimicking the real-world business scenario. In trying to achieve […]. The post Overview of MLOps With Open Source Tools appeared first on Analytics Vidhya.
DataKitchen
JANUARY 17, 2022
The post A busy year ahead in low-code and no-code development first appeared on DataKitchen.
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David Menninger's Analyst Perspectives
JANUARY 11, 2022
Organizations today are working with multiple applications and systems, including enterprise resource planning (ERP), customer relationship management (CRM), supply chain management (SCM) and other systems, where data can easily become fragmented and siloed. And as the organization increases its data sources and adds more systems and custom applications, it becomes challenging to manage the data consistently and keep data definitions up to date.
O'Reilly on Data
JANUARY 11, 2022
Every year starts with a round of predictions for the new year, most of which end up being wrong. But why fight against tradition? Here are my predictions for 2022. The safest predictions are all around AI. We’ll see more “AI as a service” (AIaaS) products. This trend started with the gigantic language model GPT-3. It’s so large that it really can’t be run without Azure-scale computing facilities, so Microsoft has made it available as a service, accessed via a web API.
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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have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth.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.
datapine
JANUARY 6, 2022
Table of Contents. 1) What Is Data Interpretation? 2) How To Interpret Data? 3) Why Data Interpretation Is Important? 4) Data Analysis & Interpretation Problems. 5) Data Interpretation Techniques & Methods. 6) The Use of Dashboards For Data Interpretation. Data analysis and interpretation have now taken center stage with the advent of the digital age… and the sheer amount of data can be frightening.
KDnuggets
JANUARY 24, 2022
What does the data reveal if we ask: "What are the 10 Best Python Courses?". Collecting almost all of the courses from top platforms shows there are plenty to choose from, with over 3000 offerings. This article summarizes my analysis and presents the top three courses.
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
DataKitchen
JANUARY 7, 2022
The post Trend-Setting Products in Data and Information Management for 2022 first appeared on DataKitchen.
David Menninger's Analyst Perspectives
JANUARY 31, 2022
I’m proud to share Ventana Research’s 2022 Market Agenda for Digital Technology. Our focus in this agenda is to deliver expertise to help organizations prioritize technology investments that increase workforce effectiveness and organizational agility, ensuring ongoing operations during any type of disruption.
TDAN
JANUARY 18, 2022
Imagine what it would be like if your data was perfect. By perfect I mean fit for use and high quality. By perfect I mean that the people in your organization have confidence in the data to use it for effective decision making and to focus on building efficiency and effectiveness through data into your […].
Timo Elliott
JANUARY 3, 2022
Back in the 1960s, a pair of radio astronomers were busily collecting data on distant galaxies. They had been doing this for years. Elsewhere, other astronomers had been doing the same. But what set these astronomers apart – and eventually earned them a Nobel Prize – was what they eventually found in the data. Like other radio astronomers, they had long detected a consistent noise pattern.
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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?
KDnuggets
JANUARY 21, 2022
Just like tradespeople need to grow in their skill sets, data scientists must also grow in the ever-changing world we inhabit. With that said, let’s break down how you can evolve your data science skills while progressing your career.
Analytics Vidhya
JANUARY 21, 2022
This article was published as a part of the Data Science Blogathon. In this article, we are going to analyze the Zero-crossing rates (ZCRs) of different music genre tracks. This post is inspired by Valerio Valerdo’s work. I highly encourage you to check out his Youtube channel for his outstanding work in the field of ML/DL […]. The post Analysis of Zero Crossing Rates of Different Music Genre Tracks appeared first on Analytics Vidhya.
DataKitchen
JANUARY 3, 2022
The post Data Science and AI Predictions for 2022 first appeared on DataKitchen.
Smart Data Collective
JANUARY 17, 2022
Did you know that global businesses are expected to spend $274 billion on big data this year? That figure is projected to grow at a rapid pace for years to come. The healthcare sector, in particular, has discovered a number of benefits of leveraging data technology. There are a lot of reasons that big data can be useful for healthcare businesses of all sizes.
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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.
TDAN
JANUARY 5, 2022
Introduction Privacy engineering, as a discrete discipline or field of inquiry and innovation, may be defined as using engineering principles and processes to build controls and measures into processes, systems, components, and products that enable the authorized, fair, and legitimate processing of personal information. One privacy leader defines it as the “inclusion and implementation of […].
Juice Analytics
JANUARY 4, 2022
You are the narrator of your data story. With great power comes great responsibility. You’ll need to do the following things: Set the Context. Explain what the data story is about and why your audience should care. Describe the Charts What measures and dimensions are being shown? How should the chart be interpreted? Guide the Flow. What should the reader look at next?
KDnuggets
JANUARY 21, 2022
Your first job is always going to be frightening. You will feel anxious and nervous to speak your own opinion. I will go through a few points that I believe everybody should incorporate into their work and personal life.
Analytics Vidhya
JANUARY 17, 2022
This article was published as a part of the Data Science Blogathon. Introduction A few days ago, I came across a question on “Quora” that boiled down to: “How can I learn Natural Language Processing in just only four months?” Then I began to write a brief response. Still, it quickly snowballed into a detailed explanation […].
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.
DataKitchen
JANUARY 3, 2022
Business analysts often find themselves in a no-win situation with constraints imposed from all sides. Their business unit colleagues ask an endless stream of urgent questions that require analytic insights. Business analysts must rapidly deliver value and simultaneously manage fragile and error-prone analytics production pipelines. Data tables from IT and other data sources require a large amount of repetitive, manual work to be used in analytics.
Smart Data Collective
JANUARY 9, 2022
Savvy business owners recognize the importance of investing in big data technology. Companies that utilize big data strategically end up having a strong advantage against their competitors. However, despite the benefits big data provides, companies that are using it are in the minority. Only 30% of companies have a well-defined data strategy. An even smaller number of companies have a data strategy that is supported by the company leadership.
Timo Elliott
JANUARY 6, 2022
Like the proverbial man looking for his keys under the streetlight , when it comes to enterprise data, if you only look at where the light is already shining, you can end up missing a lot. In a previous blog , I explored the value of dark data and how it can reveal insights that can streamline processes, improve customer experiences, generate more revenue – and maybe even help make the world a better place.
David Menninger's Analyst Perspectives
JANUARY 21, 2022
Organizations today have huge volumes of data across various cloud and on-premises systems which keep growing by the second. To derive value from this data, organizations must query the data regularly and share insights with relevant teams and departments. Automating this process using natural language processing (NLP) and artificial intelligence and machine learning (AI/ML) enables line-of-business personnel to query the data faster, generate reports themselves without depending on IT, and make
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.
KDnuggets
JANUARY 19, 2022
The landscape of programming languages is rich and expanding, which can make it tricky to focus on just one or another for your career. We highlight some of the most popular languages that are modern, widely used, and come with loads of packages or libraries that will help you be more productive and efficient in your work.
Analytics Vidhya
JANUARY 13, 2022
This article was published as a part of the Data Science Blogathon. […]. The post NLP Tutorials Part -I from Basics to Advance appeared first on Analytics Vidhya.
DataKitchen
JANUARY 25, 2022
Analytics are prone to frequent data errors and deployment of analytics is slow and laborious. The strategic value of analytics is widely recognized, but the turnaround time of analytics teams typically can’t support the decision-making needs of executives coping with fast-paced market conditions. Perhaps it is no surprise that the average tenure of a CDO or CAO is only about 2.5 years.
Smart Data Collective
JANUARY 13, 2022
Savvy business owners need to appreciate the benefits of using AI technology to make the most out of their business models. Entrepreneurs considering purchasing existing businesses have discovered that AI technology can be highly useful. You can use AI technology when you are considering purchasing a new website. You will be able to tell whether the site is likely to be profitable and provide enough of a sustainable revenue stream to make up for the investment.
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.
Depict Data Studio
JANUARY 25, 2022
Are you working on a dashboard at your workplace? Maybe you’re making a brand-new dashboard? Maybe you’re revamping an existing dashboard to bring it up to speed? Maybe you don’t have a dashboard yet, and you’re wondering if you need one? In this article, you’ll see my 10 worst mistakes from past dashboards. I’ve made all these mistakes (and more…) over the past 15 years.
Occam's Razor
JANUARY 4, 2022
I was reading a paper by a respected industry body that started by flagging head fake KPIs. I love that moniker, head fake. Likes. Sentiment/Comments. Shares. Yada, yada, yada. This is great. We can all use head fake metrics to calling out useless activity metrics. [ I would add other head fake KPIs to the list: Impressions. Reach. CPM. Cost Per View.
KDnuggets
JANUARY 17, 2022
Also: Top Five SQL Window Functions You Should Know For Data Science Interviews; A Deep Look Into 13 Data Scientist Roles and Their Responsibilities; SQL Interview Questions for Experienced Professionals; Why Do Machine Learning Models Die In Silence?
Analytics Vidhya
JANUARY 4, 2022
This article was published as a part of the Data Science Blogathon. Overview In this article, we will be predicting that whether the patient has diabetes or not on the basis of the features we will provide to our machine learning model, and for that, we will be using the famous Pima Indians Diabetes Database. Image […]. The post Diabetes Prediction Using Machine Learning appeared first on Analytics Vidhya.
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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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