Analytics Vidhya
NOVEMBER 30, 2022
This article was published as a part of the Data Science Blogathon. Introduction Source: Image by Gerd Altmann from Pixabay Smart contracts are blockchain-based computer programs that activate at predefined times. In most cases, they are used to eliminate the need for a third party during the execution of a contract, allowing all parties to […].
CIO Business Intelligence
NOVEMBER 22, 2022
Every enterprise needs a data strategy that clearly defines the technologies, processes, people, and rules needed to safely and securely manage its information assets and practices. As with just about everything in IT, a data strategy must evolve over time to keep pace with evolving technologies, customers, markets, business needs and practices, regulations, and a virtually endless number of other priorities.
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David Menninger's Analyst Perspectives
NOVEMBER 29, 2022
In today’s data-driven world, organizations need real-time access to up-to-date, high-quality data and analysis to keep pace with changing market dynamics and make better strategic decisions. By mining meaningful insights from enterprise data quickly, they gain a competitive advantage in the market. Yet, organizations face a multitude of challenges when transitioning into an analytics-driven enterprise.
Jen Stirrup
NOVEMBER 15, 2022
Information is pretty thin stuff, unless mixed with experience. – Clarence Day (1874–1935), American essayist. Why do organizations get stuck with their data? It is such a fundamental question. Often, this problem can be due to the organization concentrating solely on technology and data. However, organizations can be supported by a synergistic approach by integrating systems thinking with the data strategy and technical perspective.
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KDnuggets
NOVEMBER 29, 2022
First steps to learning data science & machine learning are the foundations.
Smart Data Collective
NOVEMBER 2, 2022
Big data technology has changed the future of marketing in a multitude of ways. A growing number of organizations are leveraging big data to get higher ROIs from their organic and paid marketing campaigns. As a result, companies around the world spent over $52 billion on data-driven marketing solutions in 2021. The Fintech sector is among those most reliant on data-driven marketing.
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
CIO Business Intelligence
NOVEMBER 21, 2022
The age-old debate on technology versus human capability remains inconclusive. But in this time of artificial intelligence (AI), analytics, and cloud, we’re seeing more opportunities to think of how humans and machines can come together as a team, rather than acting against each other. From diagnosing diseases and delivering effortless customer experiences to understanding human preferences and providing new customer insights, the human and AI partnership is evolving — and more in sync than ever
David Menninger's Analyst Perspectives
NOVEMBER 16, 2022
If you’ve ever been to London, you are probably familiar with the announcements on the London Underground to “mind the gap” between the trains and the platform. I suggest we also need to mind the gap between data and analytics. These worlds are often disconnected in organizations and, as a result, it limits their effectiveness and agility.
datapine
NOVEMBER 15, 2022
Table of Contents. 1) What Are Product Metrics? 2) Types Of Product Metrics. 3) Product Metrics Examples You Can Use. 4) Product Metrics Framework. Managing to develop an effective product roadmap goes beyond a product manager’s (PM) vision or intuition, even if these aspects matter as well. In an increasingly data-driven business world, the product management field isn’t exempt from this need.
KDnuggets
NOVEMBER 23, 2022
There exist so many great computational tools available for Data Scientists to perform their work. However, mathematical skills are still essential in data science and machine learning because these tools will only be black-boxes for which you will not be able to ask core analytical questions without a theoretical foundation.
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
Smart Data Collective
NOVEMBER 20, 2022
Proper marketing and sales prospects play a huge role in improving the success rate of your business. The strategy can either be offline or digital. However, digital marketing has become the major focus of marketers across all industries, mainly due to how customers interact and engage with modern businesses. Seeing an opportunity and knowing how and when to take advantage of it defines the majority of where today’s marketers stand.
Analytics Vidhya
NOVEMBER 7, 2022
This article was published as a part of the Data Science Blogathon. Introduction FaceIO is a cross-browser framework for user facial recognition authentication. Any website can use a JavaScript snippet to implement it. As more and more daily tasks are managed electronically rather than with pen and paper or face-to-face, the demand for quick and […].
CIO Business Intelligence
NOVEMBER 22, 2022
Digital transformation initiatives have picked up in the retail sector in recent years as store chains compete for brand awareness and sales in a rapidly evolving market. By 2026, retailers’ global investments in digital transformation tools are expected to reach $388 billion , growing by 18% a year. That may sound like retail leaders are all in , ready to use new technology tools to extract maximum value out of their operations; ready to embrace change and grab the future by the horns.
David Menninger's Analyst Perspectives
NOVEMBER 22, 2022
In my previous perspectives on cloud computing, I addressed some of the realities of cloud costs as well as hybrid and multi-cloud architectures. In the midst of the pandemic, my colleague, Mark Smith, authored a series of perspectives on considerations for business continuity in general, beginning with this look at some of the investments organizations must make to mitigate the risk of business disruptions.
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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.
DataKitchen
NOVEMBER 28, 2022
Part 4: Reviewing the Benefits. This is the final post in DataKitchen’s four-part series on DataOps Observability. Observability is a methodology for providing visibility of every journey that data takes from source to customer value across every tool, environment, data store, team, and customer so that problems are detected and addressed immediately.
KDnuggets
NOVEMBER 23, 2022
Yellowbrick for creating machine learning plots with less code.
Smart Data Collective
NOVEMBER 20, 2022
Data analytics is unquestionably one of the most disruptive technologies impacting the manufacturing sector. Manufacturers are projected to spend nearly $10 billion on analytics by the end of the year. Data analytics can solve many of the biggest challenges that manufacturers face. One of the most significant benefits of leveraging analytics in manufacturing is with marketing optimization and automation.
Analytics Vidhya
NOVEMBER 15, 2022
This article was published as a part of the Data Science Blogathon. Introduction Hierarchical clustering is one of the most famous clustering techniques used in unsupervised machine learning. K-means and hierarchical clustering are the two most popular and effective clustering algorithms. The working mechanism they apply in the backend allows them to provide such a […].
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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.
CIO Business Intelligence
NOVEMBER 17, 2022
By Milan Shetti, CEO Rocket Software In today’s fast-paced digital business world, organizations have become highly adaptive and agile to keep up with the ever-evolving demands of consumers and the market. This has pushed many organizations to accelerate their digital transformation efforts in order to remain competitive and better serve their constituents — and there is no sign of slowing down.
Timo Elliott
NOVEMBER 22, 2022
Simon Jarke is the Head of Corporate Digital Business Innovation at Freudenberg, a family-owned global technology group headquartered in Germany and founded in 1849. He recently explained how the organization has taken advantage of the latest technology advances to give business people more agility and control over their processes, without sacrificing standardization and efficiency: “I think the key to success, especially in times of digital transformation, lies in the philosophy and pract
DataKitchen
NOVEMBER 18, 2022
Part 3: Considering the Elements of Data Journeys. This is the third post in DataKitchen’s four-part series on DataOps Observability. Observability is a methodology for providing visibility of every journey that data takes from source to customer value across every tool, environment, data store, team, and customer so that problems are detected and addressed immediately.
KDnuggets
NOVEMBER 18, 2022
The Pandas library is core to any Data Science work in Python. This introduction will walk you through the basics of data manipulating, and features many of Pandas important features.
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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.
Smart Data Collective
NOVEMBER 24, 2022
Artificial intelligence is playing an important role in modern creative professions. There are a lot of reasons a growing number of companies are turning to AI technology. One poll showed that 61% of companies found that AI and machine learning were their best data investments. One of the industries that is evolving by adopting new AI tools in web design.
Analytics Vidhya
NOVEMBER 15, 2022
This article was published as a part of the Data Science Blogathon. Introduction Voting ensembles are the ensemble machine learning technique, one of the top-performing models among all machine learning algorithms. As voting ensembles are the most used ensemble techniques, there are lots of interview questions related to this topic that are asked in data […].
CIO Business Intelligence
NOVEMBER 14, 2022
Decision support systems definition A decision support system (DSS) is an interactive information system that analyzes large volumes of data for informing business decisions. A DSS supports the management, operations, and planning levels of an organization in making better decisions by assessing the significance of uncertainties and the tradeoffs involved in making one decision over another.
DataRobot Blog
NOVEMBER 1, 2022
Can artificial intelligence predict outcomes of a football (soccer) game? In a special project created to celebrate the world’s biggest football tournament, the DataRobot team set out to determine the likelihood of a team scoring a goal based on various on-the-field events. My Dad is a big football (soccer) fan. When I was growing up, he would take his three daughters to the home games of Maccabi Haifa, the leading football team in the Israeli league.
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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?
DataKitchen
NOVEMBER 18, 2022
. Question: What is the difference between Data Quality and Observability in DataOps? Data Quality is static. It is the measure of data sets at any point in time. Data Observability is dynamic — it is the testing of data, integrated data, and tools acting upon data — as it is processed — that checks for flow rates and data errors.
KDnuggets
NOVEMBER 16, 2022
While different ways to learn Data Science for the first time exist, the approach that works for you should be based on how you learn best. One powerful method is to evolve your learning from simple practice into complex foundations, as outlined in this learning path recommended by a physicist who turned into a Data Scientist.
Smart Data Collective
NOVEMBER 12, 2022
Data has unquestionably had a huge impact on our lives. It is becoming more prolific as well, as 2.5 quintillion bytes of data are generated every day. Data is everything in today’s tech-driven world. Every company collects data , analyzes it, and makes its marketing and sales strategies based on the data’s results to attract more customers and increase sales and profits.
Analytics Vidhya
NOVEMBER 14, 2022
This article was published as a part of the Data Science Blogathon Introduction In this article, we will discuss DevOps, two phases of DevOps, its advantages, and why we need DevOps along with CI and CD Pipelines. Before DevOps, software development teams, quality assurance (QA) teams, security, and operations would test the code for several […].
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