The Benefits and Drawbacks of DataOps in Practice
DataKitchen
NOVEMBER 12, 2021
The post The Benefits and Drawbacks of DataOps in Practice first appeared on DataKitchen.
DataKitchen
NOVEMBER 12, 2021
The post The Benefits and Drawbacks of DataOps in Practice first appeared on DataKitchen.
David Menninger's Analyst Perspectives
NOVEMBER 16, 2021
Talend is a data integration and management software company that offers applications for cloud computing, big data integration, application integration, data quality and master data management. The platform enables personnel to work with relational databases, Apache Hadoop, Spark and NoSQL databases for cloud or on-premises jobs. Talend data integration software offers an open and scalable architecture and can be integrated with multiple data warehouses, systems and applications to provide a un
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Analytics Vidhya
NOVEMBER 29, 2021
This article was published as a part of the Data Science Blogathon. SQL stands for Structured Query Language which is used to deal with Relational Databases to query from and manipulate databases. In the field of Data Science most of the time you are supposed to fetch the data from any RDBMS and run some […]. The post A Complete Beginner-Friendly Guide to SQL for Data Science appeared first on Analytics Vidhya.
KDnuggets
NOVEMBER 29, 2021
The hiring run for data scientists continues along at a strong clip around the world. But, there are other emerging roles that are demonstrating key value to organizations that you should consider based on your existing or desired skill sets.
Speaker: Timothy Chan, PhD., Head of Data Science
Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.
Smart Data Collective
NOVEMBER 21, 2021
If you have not lived under a rock for several years, you have undoubtedly heard about artificial intelligence (AI). However, how might artificial intelligence be used in e-commerce operations? Artificial intelligence (AI) is starting to fill every facet of our daily lives. For example, self-checkout cash registers, airport security checks, and other automated processes all use artificial intelligence to some degree.
Juice Analytics
NOVEMBER 22, 2021
Whether you are a consultant, marketer, researcher, or financial analyst…a big part of your job is presenting data. It takes a special combination of skills to articulate your insights and support them with effectively visualized data. You need to be part salesperson, part data analyst, and part author. We’ve collected 11 of the most useful tips and resources to help you improve how you present data.
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David Menninger's Analyst Perspectives
NOVEMBER 9, 2021
How does your organization define and display its metrics? I believe many organizations are not defining and displaying metrics in a way that benefits them most. If an organization goes through the trouble of measuring and reporting on a metric, the analysis ought to include all the information needed to evaluate that metric effectively. A number, by itself, does not provide any indication of whether the result is good or bad.
Analytics Vidhya
NOVEMBER 23, 2021
This article was published as a part of the Data Science Blogathon. Overview. Regression analysis is used to solve problems of prediction based on data statistical parameters. In this article, we will look at the use of a polynomial regression model on a simple example using real statistic data. We will analyze the relationship between […]. The post Building an end-to-end Polynomial Regression Model in R appeared first on Analytics Vidhya.
KDnuggets
NOVEMBER 23, 2021
Sure, we all make mistakes -- which can be a bit more painful when we are trying to get hired -- so check out these typical errors applicants make while answering SQL questions during data science interviews.
Smart Data Collective
NOVEMBER 17, 2021
More companies than ever are being driven by data. They use a number of important data analytics tools to help implement their functions more efficiently. Unfortunately, big data can be mysterious for many companies. Only 13% of companies with data strategies are meeting the objectives outlined in them. They need to know how to use it effectively to get the most value out of it.
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.
Juice Analytics
NOVEMBER 2, 2021
How to get started with data storytelling? For the beginner — and even for the experienced data analyst or data scientist — data storytelling can be a vague, disorientating concept. This question posted on Reddit is a good example of the interest and confusion about the topic: …which was then followed by this pure-gold response: I hope to make data storytelling a bit more accessible by laying out some of the basic concepts and skills required.
DataKitchen
NOVEMBER 4, 2021
The post The vast majority of data engineers are burnt out. Those working in healthcare are no exception first appeared on DataKitchen.
David Menninger's Analyst Perspectives
NOVEMBER 24, 2021
Organizations have become more agile and responsive, in part, as a result of being more agile with their information technology. Adopting a DevOps approach to application deployment has allowed organizations to deploy new and revised applications more quickly. DataOps is enabling organizations to be more agile in their data processes. As organizations are embracing artificial intelligence (AI) and machine learning (ML), they are recognizing the need to adopt MLOps.
Analytics Vidhya
NOVEMBER 21, 2021
This article was published as a part of the Data Science Blogathon. Humankind has always looked up to the stars. Since the dawn of civilization, we have mapped constellations, named planets after Gods and so on. We have seen signs and visions in celestial bodies. In the previous century, we finally had the technology to […]. The post Using Data Visualization to Explore the Human Space Race!
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.
KDnuggets
NOVEMBER 19, 2021
The terms ‘data science’ and ‘machine learning’ are often used interchangeably. But while they are related, there are some glaring differences, so let’s take a look at the differences between the two disciplines, specifically as it relates to programming.
Smart Data Collective
NOVEMBER 1, 2021
Machine learning technology has become an integral part of many different design processes. Many entrepreneurs use machine learning to improve logo designs. However, there are a lot of other benefits as well. One of the areas where machine learning has proven particularly useful has been with 3D printing. 3D Printing is Crucial for Cost Optimization in 3D Printing.
Juice Analytics
NOVEMBER 11, 2021
When it comes to using data, many organizations are reminiscent of the famous poem “Rime of the Ancient Mariner”: “Water, water, every where, Nor any drop to drink”. Data is everywhere, but it seldom seems to quench the thirst for smarter decisions. (As a side-note, this poem originated the phrase “albatross around your neck” — which is how a lot of CIOs and CTOs feel with both the data and expectations.
DataKitchen
NOVEMBER 2, 2021
The post Battle for Data Pros Heats Up as Burnout Builds first appeared on DataKitchen.
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Mark Raskino
NOVEMBER 1, 2021
[Reminder – these blogs are analyst personal opinion, not Gartner published research]. “Open up your firewalls to let your people access us!” said Philip Rosedale, founder of Second Life, as I recall. He was being interviewed on stage by my colleague Steve Prentice (now retired), who asked what the hundreds of CIOs and IT leaders in the audience could do to advance corporate use of immersive virtual worlds for business.
Analytics Vidhya
NOVEMBER 15, 2021
This article was published as a part of the Data Science Blogathon Introduction In this article, you will learn how to build a face-recognition system using Python. Face recognition is a step further to face detection. In face detection, we only detect the location of the human face in an image but in face recognition, we […]. The post Build Face Recognition Attendance System using Python appeared first on Analytics Vidhya.
KDnuggets
NOVEMBER 18, 2021
Natural language processing research and applications are moving forward rapidly. Several trends have emerged on this progress, and point to a future of more exciting possibilities and interesting opportunities in the field.
Smart Data Collective
NOVEMBER 12, 2021
One of the best things about digital marketing is that it’s often at the forefront of the latest online technologies. It doesn’t get any more cutting-edge at the moment than machine learning, and it’s not only large companies that have already started to take advantage. As far back as 2018, a veritable eternity in the world of online marketing, over 80% of marketing organizations reported the deployment or growth of their AI and machine learning efforts.
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.
Cloudera
NOVEMBER 19, 2021
We are excited by the endless possibilities of machine learning (ML). We recognise that experimentation is an important component of any enterprise machine learning practice. But, we also know that experimentation alone doesn’t yield business value. Organizations need to usher their ML models out of the lab (i.e., the proof-of-concept phase) and into deployment, which is otherwise known as being “in production”. .
Dataiku
NOVEMBER 18, 2021
Many of you reading this will either have first-hand experience with the challenges of achieving data-driven success within financial firms or will have a reasonable concern that such success will not come easily to your organization. It is certainly true that finding actionable insights within your organizations — and then actually taking meaningful action based on those insights — is not a trivial matter.
TDAN
NOVEMBER 2, 2021
What is Data Governance and How Do You Measure Success? Data governance is a system for answering core questions about data. It begins with establishing key parameters: What is data, who can use it, how can they use it, and why? Answers will differ widely depending upon a business’ industry and growth strategy. But what […].
Analytics Vidhya
NOVEMBER 21, 2021
This article was published as a part of the Data Science Blogathon. What is Power BI? Microsoft‘s business analytics product, Power BI, delivers interactive data visualization BI capabilities that allow users to see and share data and insights throughout their organisation. Power BI provides insight data by using data interactively and exploring it by visualizations. […].
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Outdated or absent analytics won’t cut it in today’s data-driven applications – not for your end users, your development team, or your business. That’s what drove the five companies in this e-book to change their approach to analytics. Download this e-book to learn about the unique problems each company faced and how they achieved huge returns beyond expectation by embedding analytics into applications.
KDnuggets
NOVEMBER 2, 2021
ML pipeline design has undergone several evolutions in the past decade with advances in memory and processor performance, storage systems, and the increasing scale of data sets. We describe how these design patterns changed, what processes they went through, and their future direction.
Smart Data Collective
NOVEMBER 12, 2021
Much has changed since the time when organizations only knew of antiviruses and simple firewalls as the tools, they need to protect their computers. To address newer challenges, security providers have developed new technologies and strategies to combat evolving threats. Stephanie Benoit-Kurtz, Lead Area Faculty Chair for the University of Phoenix’s Cybersecurity Programs, offers a good summary of the changes security organizations should anticipate , especially in the time of the pandemic.
Teradata
NOVEMBER 22, 2021
Teradata's Martin Willcox recently passed 17 years at Teradata and a quarter of a century in the industry. Here are the ten things he's learned about data analytics in those 20-odd years.
Dataiku
NOVEMBER 19, 2021
14 years ago I (Doug) met with the director of business intelligence at NCR in his old headquarters in Dayton, Ohio. He’d recently finished a BusinessObjects implementation and proudly told me that he had 400 reports in production. I really didn’t have an understanding of that so I asked, “Is that too many or not enough?” It was obvious that he’d never considered the question, as a look of shock came over his face.
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