August, 2021

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How DataOps is Transforming Commercial Pharma Analytics

DataKitchen

DataOps has become an essential methodology in pharmaceutical enterprise data organizations, especially for commercial operations. Companies that implement it well derive significant competitive advantage from their superior ability to manage and create value from data. They will be able to produce high-quality, on-demand insight that consistently leads to successful business decisions.

Analytics 246
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Must know Pandas Functions for Machine Learning Journey

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction Do you wish you could perform this function using Pandas. Well, there is a good possibility you can! For data scientists who use Python as their primary programming language, the Pandas package is a must-have data analysis tool. The Pandas package has everything […].

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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 And it’s not being superseded by artificial intelligence.

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Understanding the Basics of Apache Spark RDD

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Hello readers! In this article, I am going to discuss one of the most essential parts of Apache Spark called RDD. Before getting into Spark RDD, I strongly recommend you to read my article, Understand the internal working of Apache Spark to get an overview of […]. The post Understanding the Basics of Apache Spark RDD appeared first on Analytics Vidhya.

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The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Communication

Speaker: David Bard, Principal at VP Product Coaching

In the fast-paced world of digital innovation, success is often accompanied by a multitude of challenges - like the pitfalls lurking at every turn, threatening to derail the most promising projects. But fret not, this webinar is your key to effective product development! Join us for an enlightening session to empower you to lead your team to greater heights.

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When the Voice of the Customer Actually Talks

Rocket-Powered Data Science

For many years, organizations (mostly consumer-facing) have placed the “voice of the customer” (VoC) high on their priority list of top sources for customer intelligence. The goals of such activities are to improve customer service, customer interactions, customer engagement, and customer experience (CX) through just-in-time customer assistance, personalization, and loyalty-building activities.

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Sisense Earns Analytics Digital Innovation Award for 2021

David Menninger's Analyst Perspectives

The annual Ventana Research Digital Innovation Awards showcase advances in the productivity and potential of business applications, as well as technology that contributes significantly to the improved processes and performance of an organization. Our goal is to recognize technology and vendors that have introduced noteworthy digital innovations to advance business and IT.

Analytics 242

More Trending

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The Role of Model Governance in Machine Learning and Artificial Intelligence

Domino Data Lab

In the world of machine learning (ML) and artificial intelligence (AI), governance is a lifelong pursuit. All models require testing and auditing throughout their deployment and, because models are continually learning, there is always an element of risk that they will drift from their original standards. As such, model governance needs to be applied to each model for as long as it’s being used.

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How to Win New Business with External Data

TDAN

Increasingly, external data (alternative data, public data, open data – call it what you want) is being called the “secret sauce” of driving advanced analytics, developing machine learning and AI capabilities, enriching existing models, and delivering unrealized insights to every part of your organization. The difficulty in connecting to this data is top of mind for […].

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Effective Data Visualization Techniques in Data Science Using Python

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Data Visualization Data Visualization techniques involve the generation of graphical or. The post Effective Data Visualization Techniques in Data Science Using Python appeared first on Analytics Vidhya.

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10 Tips to Visualize Data Like a Pro

Juice Analytics

Have you nailed all the data visualization basics? Stuff like… ?You know pie charts are bad except in certain specific use cases; ?You can spot chartjunk from a mile away; ?You confidently pick the right kind of chart based on what you want to emphasize in the data; ?You use just the right amount of color to bring meaning, but not so much as to distract; ?

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Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

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Understanding the Differences Between Data Lakes and Data Warehouses

Smart Data Collective

Data lakes and data warehouses are probably the two most widely used structures for storing data. In this article, we will explore both, unfold their key differences and discuss their usage in the context of an organization. Data Warehouses and Data Lakes in a Nutshell. A data warehouse is used as a central storage space for large amounts of structured data coming from various sources.

Data Lake 139
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Addressing Data Mesh Technical Challenges with DataOps

DataKitchen

Below is our third post (3 of 5) on combining data mesh with DataOps to foster greater innovation while addressing the challenges of a decentralized architecture. We’ve talked about data mesh in organizational terms (see our first post, “ What is a Data Mesh? ”) and how team structure supports agility. Let’s take a look at some technical aspects of data mesh so we can work our way towards a pharmaceutical industry application example. .

Testing 246
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What’s the Link Between AI Governance, MLOps, and Responsible AI? Scaling AI

Dataiku

We are taking a break on the AI regulation series to take a step back and clarify the connection between AI Governance, MLOps, and Responsible AI. These three concepts fall off the tip of the tongues of industry practitioners, researchers, and regulators alike, all without having clearly defined connections or boundaries. At Dataiku , we believe that these concepts are central pieces of being able to scale with AI.

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Big Data Modeling Improves Business Intelligence

TDAN

Through big data modeling, data-driven organizations can better understand and manage the complexities of big data, improve business intelligence (BI), and enable organizations to benefit from actionable insight. Big data modeling is an extension of data modeling, a practice adopted by many areas of Information Technology (IT), used to better understand enterprise data resources.

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How to Build an Experimentation Culture for Data-Driven Product Development

Speaker: Margaret-Ann Seger, Head of Product, Statsig

Experimentation is often seen as an aspirational practice, especially at smaller, fast-moving companies who are strapped for time and resources. So, how can you get your team making decisions in a more data-driven way while continuing to remain lean and maintaining ship velocity? In this webinar, Margaret-Ann Seger, Head of Product at Statsig, will teach you how to build an experimentation culture from the ground-up, graduating from just getting started with data-driven development to operating

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Hyperparameter Tuning Of Neural Networks using Keras Tuner

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction In neural networks we have lots of hyperparameters, it is. The post Hyperparameter Tuning Of Neural Networks using Keras Tuner appeared first on Analytics Vidhya.

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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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Leveraging Data Science To Grow And Manage Your Team

Smart Data Collective

When applied to the hiring process, data analytics can help you strategically grow and manage your team with greater accuracy and success. More companies are using big data to create a stronger company culture. 50% of business owners consider big data to be the most effective hiring method, a Global Recruiting Trends survey reveals. Moreover, big data can also improve talent retention by 56% and better clarify skills gaps by 50%.

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What is a Data Mesh?

DataKitchen

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. With an architecture comprised of numerous domains, enterprises need to manage order-of-operations issues, inter-domain communication, and shared services like environment creation and meta-orchestration. A DataOps superstructure provides the foundation to address the many challenges inherent in operating a group of interdependent domains.

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Entity Resolution Checklist: What to Consider When Evaluating Options

Are you trying to decide which entity resolution capabilities you need? It can be confusing to determine which features are most important for your project. And sometimes key features are overlooked. Get the Entity Resolution Evaluation Checklist to make sure you’ve thought of everything to make your project a success! The list was created by Senzing’s team of leading entity resolution experts, based on their real-world experience.

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A ‘Fresh Squeeze on Data’ to Help Children Learn about Data, AI and Machine Learning

Cloudera

Dear Parents and Educators and Friends of Cloudera, If you are reading this blog, you know us at Cloudera as a group of self-described data geeks and data analysts. We believe data drives better decisions and moves businesses forward and for us, that’s exciting. We are innovating and helping Fortune 500 transform and grow because they can make better data-driven decisions at the accelerated pace we live and work in today.

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Differences Between Data Management and Data Governance

TDAN

A common misconception among c-level executives is that governance and management of data is the same thing other than in capital letters. Yet, there are some crucial differences between these two terms that should be understood before working on a project or implementing a program. Below, we will explore the main differences between Data Management […].

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Python Tutorial: Working with CSV file for Data Science

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Source Intro: In this article, I will walk you. The post Python Tutorial: Working with CSV file for Data Science appeared first on Analytics Vidhya.

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Dataiku Series E: Unleashing Everyday AI

Dataiku

“AI is starting to deliver on its potential” — it feels like years that people have been singing variations of this refrain, doesn’t it? And while organizations have come a long way with AI, I don’t think we’ve even scratched the surface when it comes to business potential with and value from AI. That’s why today, we’re proud to announce a $400 million Series E funding round that will allow Dataiku to unleash Everyday AI within exponentially more organizations around the world.

IT 122
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Strategic CX: A Deep Dive into Voice of the Customer Insights for Clarity

Speaker: Nicholas Zeisler, CX Strategist & Fractional CXO

The first step in a successful Customer Experience endeavor (or for that matter, any business proposition) is to find out what’s wrong. If you can’t identify it, you can’t fix it! 💡 That’s where the Voice of the Customer (VoC) comes in. Today, far too many brands do VoC simply because that’s what they think they’re supposed to do; that’s what all their competitors do.

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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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4 Ways Conversational AI Is Improving the Customer Experience

DataKitchen

The post 4 Ways Conversational AI Is Improving the Customer Experience first appeared on DataKitchen.

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Embedded Foodservice Analytics Feed Users’ Need for Data

Sisense

Blog. COVID-19 is a huge data story in many ways, and food delivery analytics are a big part of that. Online food ordering in 2020 hit $115 billion globally and could reach nearly $127 billion in 2021 according to an April 2021 report. For much of the pandemic, and through to today, diners switched from sit-down dining to takeout and delivery, a decision based as much on consumer access to data (like local infection rates) as local mandates that saw many restaurants unable to seat large numbers

Analytics 119
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None Shall Pass! Are Your Database Standards Too Rigid?

TDAN

Rigidly adhering to a standard, any standard, without being reasonable and using your ability to think through changing situations and circumstances is itself a bad standard. I guess I should quickly define what I mean by a “database standard” for those who are not aware. Database standards are common practices and procedures that are documented and […].

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Addressing Top Enterprise Challenges in Generative AI with DataRobot

The buzz around generative AI shows no sign of abating in the foreseeable future. Enterprise interest in the technology is high, and the market is expected to gain momentum as organizations move from prototypes to actual project deployments. Ultimately, the market will demand an extensive ecosystem, and tools will need to streamline data and model utilization and management across multiple environments.

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Complete guide on how to Use LightGBM in Python

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction A Gradient Boosting Decision tree or a GBDT is a. The post Complete guide on how to Use LightGBM in Python appeared first on Analytics Vidhya.

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CBAP certification: A high-profile credential for business analysts

CIO Business Intelligence

The Certified Business Analysis Professional (CBAP) is a credential for business analysts offered by the International Institute of Business Analysis (IIBA). IIBA is a nonprofit professional association founded in 2003 to promote the field of business analysis. The organization describes CBAP as a credential that “recognizes seasoned BA professionals who have over five years of practical business analysis work experience.

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5 Advanced Identity Theft Protection Tips in the Big Data Era

Smart Data Collective

There are a lot of great things about living in an era governed by big data. Big data creates a lot of new opportunities in business and our personal lives. However, there are also downsides to the sudden influx of data in the 21st Century. One major concern is that big data has made identity theft risks more significant. Addressing the Risk of Identity Theft in a World Increasingly Dependent on Big Data.

Big Data 135
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AIOps Benefits All Aspects of the Enterprise

DataKitchen

The post AIOps Benefits All Aspects of the Enterprise first appeared on DataKitchen.

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Driving Business Impact for PMs

Speaker: Jon Harmer, Product Manager for Google Cloud

Move from feature factory to customer outcomes and drive impact in your business! This session will provide you with a comprehensive set of tools to help you develop impactful products by shifting from output-based thinking to outcome-based thinking. You will deepen your understanding of your customers and their needs as well as identifying and de-risking the different kinds of hypotheses built into your roadmap.