DataKitchen
AUGUST 27, 2021
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 Vidhya
AUGUST 25, 2021
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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CIO Business Intelligence
AUGUST 11, 2021
Business intelligence is not an oxymoron like jumbo shrimp. It’s not dead. And it’s not being superseded by artificial intelligence.
Analytics Vidhya
AUGUST 30, 2021
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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Rocket-Powered Data Science
AUGUST 22, 2021
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.
David Menninger's Analyst Perspectives
AUGUST 24, 2021
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.
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
Smart Data Collective
AUGUST 25, 2021
Artificial intelligence is one of the fastest-growing technologies. It grew 270% in just four years since more companies started noticing its benefits and adopted this technology. eCommerce businesses are no exception. Over 50 percent of them use AI for various purposes, like creating personalized services and automation. This article will share the basic concept of AI, including its definition, types, and current trends.
Domino Data Lab
AUGUST 6, 2021
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.
Analytics Vidhya
AUGUST 23, 2021
This article was published as a part of the Data Science Blogathon Building a simple Machine Learning model using Pytorch from scratch. Image by my great learning Introduction Gradient descent is an optimization algorithm that is used to train machine learning models and is now used in a neural network. Training data helps the model learn […].
Juice Analytics
AUGUST 25, 2021
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; ?
Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage
When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m
TDAN
AUGUST 3, 2021
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 […].
DataKitchen
AUGUST 19, 2021
Below is our fourth post (4 of 5) on combining data mesh with DataOps to foster innovation while addressing the challenges of a decentralized architecture. We’ve covered the basic ideas behind data mesh and some of the difficulties that must be managed. Below is a discussion of a data mesh implementation in the pharmaceutical space. For those embarking on the data mesh journey, it may be helpful to discuss a real-world example and the lessons learned from an actual data mesh implementation.
Smart Data Collective
AUGUST 31, 2021
Big data has led to some remarkable changes in the field of marketing. It has been especially impactful in regards to online content marketing. Many marketers have used AI and data analytics to make more informed insights into a variety of campaigns. Data analytics tools have been especially useful with PPC marketing , media buying and other forms of paid traffic.
Occam's Razor
AUGUST 9, 2021
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.
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The DHS compliance audit clock is ticking on Zero Trust. Government agencies can no longer ignore or delay their Zero Trust initiatives. During this virtual panel discussion—featuring Kelly Fuller Gordon, Founder and CEO of RisX, Chris Wild, Zero Trust subject matter expert at Zermount, Inc., and Principal of Cybersecurity Practice at Eliassen Group, Trey Gannon—you’ll gain a detailed understanding of the Federal Zero Trust mandate, its requirements, milestones, and deadlines.
Analytics Vidhya
AUGUST 5, 2021
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.
Juice Analytics
AUGUST 8, 2021
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.
TDAN
AUGUST 3, 2021
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.
DataKitchen
AUGUST 13, 2021
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.
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GAP's AI-Driven QA Accelerators revolutionize software testing by automating repetitive tasks and enhancing test coverage. From generating test cases and Cypress code to AI-powered code reviews and detailed defect reports, our platform streamlines QA processes, saving time and resources. Accelerate API testing with Pytest-based cases and boost accuracy while reducing human error.
Smart Data Collective
AUGUST 5, 2021
Collecting, processing, and carrying out analysis on streaming data , in industries such as ad-tech involves intense data engineering. The data generated daily is huge (100s of GB data) and requires a significant processing time to process the data for subsequent steps. Another challenge is the joining of datasets to derive insights. Each process on average has more than 10 datasets and an equal number of joins with multiple keys.
Dataiku
AUGUST 25, 2021
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.
Analytics Vidhya
AUGUST 1, 2021
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.
BA Learnings
AUGUST 7, 2021
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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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.
TDAN
AUGUST 31, 2021
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 […].
DataKitchen
AUGUST 9, 2021
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. .
Smart Data Collective
AUGUST 16, 2021
Managing data is a challenge. It’s not hard to collect data, but most companies collect data in disparate locations and across multiple applications that don’t talk to each other. With this model, multiple reports are required to crunch data from multiple sources. That requires manually entering data into yet another application to generate a final report.
Domino Data Lab
AUGUST 12, 2021
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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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?
Analytics Vidhya
AUGUST 5, 2021
ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Data- a world-changing gamer is a key component for all. The post Let’s Understand All About Data Wrangling! appeared first on Analytics Vidhya.
Cloudera
AUGUST 17, 2021
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.
Dataiku
AUGUST 4, 2021
“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.
DataKitchen
AUGUST 3, 2021
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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