January, 2022

Overview of MLOps With Open Source Tools

Analytics Vidhya

This article was published as a part of the Data Science Blogathon.

A busy year ahead in low-code and no-code development


The post A busy year ahead in low-code and no-code development first appeared on DataKitchen. News News / PR


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Reltio Connects MDM in the Cloud for Business

David Menninger's Analyst Perspectives

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.

What’s ahead for AI, VR, NFTs, and more?

O'Reilly on Data

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.

4 Key Steps to Data Transformation Success with Data Mesh

It’s tougher than ever to give your clients the data and insight they need, when they need it (and how they want it) – while addressing issues like security. Find out how data mesh architectures can help you meet these challenges and more.

All in the Data: Ways to Improve Your Data

The Data Administration Newsletter

Imagine what it would be like if your data was perfect. By perfect I mean fit for use and high quality.

Query Your Pandas DataFrames with SQL


Learn how to query your Pandas DataFrames using the standard SQL SELECT statement, seamlessly from within your Python code. 2021 Oct Tutorials, Overviews SQL


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Trend-Setting Products in Data and Information Management for 2022


The post Trend-Setting Products in Data and Information Management for 2022 first appeared on DataKitchen. News News / PR

The Digital Technology Market Agenda for 2022: Innovation for Business Resilience

David Menninger's Analyst Perspectives

I’m proud to share Ventana Research’s 2022 Market Agenda for Digital Technology.

The Role and Importance of Data Collection in Healthcare

Smart Data Collective

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.

What is Privacy Engineering?

The Data Administration Newsletter

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.

Monetizing Analytics Features: Why Data Visualization Will Never Be Enough

Five years ago, data visualizations were a powerful way to differentiate a software application. Today, free visualizations seem to be everywhere. Two trends are forcing application providers to rethink how they offer analytics in their products.

Fake It Till You Make It: Generating Realistic Synthetic Customer Datasets


Finding the data you need is hard. So why not fake it? 2022 Jan Tutorials, Overviews Data Science

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Diabetes Prediction Using Machine Learning

Analytics Vidhya

This article was published as a part of the Data Science Blogathon.

Data Science and AI Predictions for 2022


The post Data Science and AI Predictions for 2022 first appeared on DataKitchen. News News / PR

ThoughtSpot Enables Simpler Analytics with AI and NLP

David Menninger's Analyst Perspectives

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.

The 2023 Supply Chain Crystal Ball: Challenges and Solutions

Speaker: Olivia Montgomery, Associate Principal Supply Chain Analyst

Curious to know how your peers are navigating ongoing disruption? In this webinar, you’ll gain actionable insights from Olivia Montgomery as she walks us through Capterra’s extensive research on how businesses - notably small and midsize businesses - are addressing supply chain challenges in 2023.

3 Huge Ways Big Data Analytics Benefits Businesses

Smart Data Collective

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.

Narrating Data Stories: Set context, explain charts, highlight insights, and guide your audience

Juice Analytics

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?

Data Science Web nugget Roundup, Jan 14: Kaggle Datasets & Python Debugging


In our first weekly roundup of data science nuggets from around the web, check out a list of curated articles on Kaggle datasets, Python debugging tools, what it is data scientists do, an overview of YOLO, 2-dimensional PyTorch tensors, and the secrets of machine learning deployment.

NLP Tutorials Part -I from Basics to Advance

Analytics Vidhya

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. Beginner NLP Python blogathon python

5 Powerful Prescriptive Analytics Examples in Supply Chain

Prescriptive analytics is a type of advanced analytics that optimizes decision-making by providing a recommended action. Supply chain, with its complex planning questions, is typically an area where optimization technology is required. Read about 5 use cases.

Fire Your Super-Smart Data Consultants with DataOps


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.

What is Dark Data, Why Does it Matter, and Why Are Humans Still Needed?

Timo Elliot

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.

AI Technology is Becoming Essential for App Store Publishers

Smart Data Collective

Artificial intelligence technology is becoming more valuable than ever. The market was estimated to be worth over $50 billion by the end of 2020 and is growing around 20% a year. One of the biggest reasons AI is growing in popularity is due to its role in mobile app design.

Why Choose a Hybrid Data Cloud in Financial Services?


As I meet with our customers, there are always a range of discussions regarding the use of the cloud for financial services data and analytics.

Intent Signal Data 101

Intent signal data helps B2B marketers engage with buyers sooner in the sales cycle. But there are many confusing terms used to describe intent data. Read this infographic to better understand three common areas of confusion.

Top Five SQL Window Functions You Should Know For Data Science Interviews


Focusing on the important concepts for data scientists. 2022 Jan Tutorials, Overviews SQL

Building Language Models in NLP

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction A language model in NLP is a probabilistic statistical model that determines the probability of a given sequence of words occurring in a sentence based on the previous words.

DataOps For Business Analytics Teams


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.

What Do We Talk About, When We Talk About Data?


Some people don’t engage with others on data and AI because they perceive a barrier between how they work with data and how they could work with data — call it an unrequited dream of something better.

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Modern Data Architecture for Embedded Analytics

Data has gone from a mere result of applications & processes to being crowned king. Picking the right avenue to data architecture depends on your organization’s needs. Development teams should build in stages, starting with a task that can be solved.

AI Underscores Passwordless Authentication Risks for Internet Users

Smart Data Collective

Advances in artificial intelligence have been shaping the state of the Internet for years. One of the biggest changes has been in the arena of cybersecurity. AI technology has been a double-edged sword for the cybersecurity sector.

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Security Reference Architecture Summary for Cloudera Data Platform


This blog will summarise the security architecture of a CDP Private Cloud Base cluster. The architecture reflects the four pillars of security engineering best practice, Perimeter, Data, Access and Visibility.

How to Process a DataFrame with Millions of Rows in Seconds


TLDR; process it with a new Python Data Processing Engine in the Cloud. 2022 Jan Tutorials, Overviews Python

TOP 10 GitHub Repositories for Data Science

Analytics Vidhya

Introduction Data science is a collaborative scientific field of computing that has grown many folds in recent years and has become the powerhouse behind the business decisions made by organizations in today’s time, be it the FAANG’s or early-stage startups.

A Deep Dive Into Supply Chain Strategy: Why Yours Isn't Working

Speaker: Michelle Meyer, Founder and CEO of MatterProviders

Michelle Meyer is here to walk you through the future of supply chain strategy, and why your current approach is probably not working. In this exclusive webinar, she will explore ways to develop and perfect your new supply chain design in this post-pandemic era of economic uncertainty.