KDnuggets
SEPTEMBER 25, 2019
As a data scientist, you can get lost in your daily dives into the data. Consider this advice to be certain to follow in your work for being diligent and more impactful for your organization.
datapine
SEPTEMBER 11, 2019
Digital data, by its very nature, paints a clear, concise, and panoramic picture of a number of vital areas of business performance, offering a window of insight that often leads to creating an enhanced business intelligence strategy and, ultimately, an ongoing commercial success. Business intelligence steps up into this process by creating a comprehensive perspective of data, enabling teams to generate actionable insights on their own.
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Analytics Vidhya
SEPTEMBER 11, 2019
Overview A data-science-driven product consists of multiple aspects every leader needs to be aware of Machine learning algorithms are one part of a whole. The post 4 Key Aspects of a Data Science Project Every Data Scientist and Leader Should Know appeared first on Analytics Vidhya.
Corinium
SEPTEMBER 16, 2019
Enterprises across the globe are waking up to the fact that data is an asset that requires its own strategy. Those that treat it as such are now seeing substantial returns on their investments.
Speaker: Tamara Fingerlin, Developer Advocate
In this new webinar, Tamara Fingerlin, Developer Advocate, will walk you through many Airflow best practices and advanced features that can help you make your pipelines more manageable, adaptive, and robust. She'll focus on how to write best-in-class Airflow DAGs using the latest Airflow features like dynamic task mapping and data-driven scheduling!
O'Reilly on Data
SEPTEMBER 26, 2019
The O’Reilly Data Show Podcast: Arun Kejariwal and Ira Cohen on building large-scale, real-time solutions for anomaly detection and forecasting. In this episode of the Data Show , I speak with Arun Kejariwal of Facebook and Ira Cohen of Anodot (full disclosure: I’m an advisor to Anodot). This conversation stemmed from a recent online panel discussion we did, where we discussed time series data, and, specifically, anomaly detection and forecasting.
David Menninger's Analyst Perspectives
SEPTEMBER 13, 2019
The Oracle Analytics Summit 2019 was the inaugural user event for Oracle Analytics customers, and they also broadcast the video for thousands of others. You can watch the keynote at [link]. Executives talked about some big organizational changes, including Bruno Aziza joining last year to lead the analytics organization. This event marked a transition and "a new beginning" for the Oracle Analytics portfolio, as the company announced three new analytics products.
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
datapine
SEPTEMBER 4, 2019
The secret is out, and has been for a while: In order to remain competitive, businesses of all sizes, from startup to enterprise, need business intelligence (BI). Business intelligence has evolved into smart solutions that provide effective data management – from extracting, monitoring, analyzing, and deriving actionable insights needed to stay competitive on the market, to powerful visualizations created with a dashboard builder which enables business users to interact with data and drill into
Analytics Vidhya
SEPTEMBER 18, 2019
Overview Writing optimized Python code is a crucial piece in your data science skillset Here are four methods to optimize your Python code (with. The post 4 Unique Methods to Optimize your Python Code for Data Science appeared first on Analytics Vidhya.
Corinium
SEPTEMBER 29, 2019
Data as an Asset. I first heard the phrase “our data is one of our biggest assets” while working in the Munich headquarters of a multinational corporation. It had been uttered by one executive or other amid a talk full of content-free phrases that I had mostly tuned out, but being related to my area of expertise, this one caught what was left of my attention.
O'Reilly on Data
SEPTEMBER 12, 2019
The O’Reilly Data Show Podcast: Michael Mahoney on developing a practical theory for deep learning. In this episode of the Data Show , I speak with Michael Mahoney , a member of RISELab , the International Computer Science Institute , and the Department of Statistics at UC Berkeley. A physicist by training, Mahoney has been at the forefront of many important problems in large-scale data analysis.
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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.
erwin
SEPTEMBER 5, 2019
Why planning your 5G roadmap requires significant input from enterprise architects. 5G is coming and bringing with it the promise to transform any industry. And while the focus has been on the benefits to consumers, the effects on the enterprise are far- reaching. Few examples of emerging technology have the potential to disrupt and downright revolutionize certain markets and processes than 5G.
KDnuggets
SEPTEMBER 30, 2019
Three new releases that will help researchers streamline the implementation of reinforcement learning programs.
datapine
SEPTEMBER 25, 2019
In the Age of Information, data equals power. By harnessing the power of your business’s most valuable digital insights, you will enhance decision-making, improve internal communication, and accelerate your success. But with so much information and such little time in the day, how do you get the most from your data? Data is most effective when it’s visual, easy to analyze, and accessible to everyone in the organization.
Analytics Vidhya
SEPTEMBER 10, 2019
Overview Sampling is a popular statistical concept – learn how it works in this article We will also talk about eight different types of. The post A Data Scientist’s Guide to 8 Types of Sampling Techniques appeared first on Analytics Vidhya.
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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?
Corinium
SEPTEMBER 26, 2019
Alternative data looks set to go mainstream. The term may have originally been used in reference to the non-traditional datasets hedge funds and investors use to get an edge on the markets. But the sheer variety of alternative datasets available today means its usage is quickly spreading to other industries and sectors.
CIO Business Intelligence
SEPTEMBER 5, 2019
There is golden knowledge in the sea of data that businesses are swimming in. Being able to fish out the business intelligence you need — when you need it — is the key to steering your ship.
Bruno Aziza
SEPTEMBER 22, 2019
Today, as data has become a lifeblood of industry leading firms, competing on analytics has become an unquestioned mantra, and firms have anointed Chief Data Officers to occupy the C-Suite.
KDnuggets
SEPTEMBER 24, 2019
Deep Learning is/has become the hottest skill in Data Science at the moment. There is a plethora of articles, courses, technologies, influencers and resources that we can leverage to gain the Deep Learning skills.
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📌Is your Data & AI transformation struggling to really impact the business? Discover the game-changing StratOps approach that: Bridges the Gap : Connect your Data & AI strategy to your operating model, to ensure alignment at every level. Prioritizes Outcomes : Focuses on concrete business outcomes from day one, rather than capabilities in isolation.
DataCamp
SEPTEMBER 12, 2019
You can become a data scientist at any age if you’re willing to put in the work.
Analytics Vidhya
SEPTEMBER 16, 2019
Overview What is PyTorch? How can you get started with it from scratch? We’ll cover all of that in this article PyTorch is one. The post A Beginner-Friendly Guide to PyTorch and How it Works from Scratch appeared first on Analytics Vidhya.
Corinium
SEPTEMBER 23, 2019
It might seem obvious that business decisions based on facts and data consistently deliver better results than those based on instinct or intuition. So, it should be no surprise that NewVantage Partners’ Big Data Executive Survey 2018 suggests that 99% of business leaders are trying to make their organizations more data-driven. What might be more surprising to some is that just a third of them are succeeding.
erwin
SEPTEMBER 19, 2019
Data governance isn’t a one-off project with a defined endpoint. It’s an on-going initiative that requires active engagement from executives and business leaders. Data governance, today, comes back to the ability to understand critical enterprise data within a business context, track its physical existence and lineage, and maximize its value while ensuring quality and security.
Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage
When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.
CIO Business Intelligence
SEPTEMBER 12, 2019
Business intelligence (BI) and analytics platforms have long been a staple for business, but thanks to the rise of self-service BI tools, responsibility for analytics has shifted from IT to business analysts, with support from data scientists and database administrators.
KDnuggets
SEPTEMBER 27, 2019
The article contains a brief introduction to various concepts related to Hierarchical clustering algorithm.
Data Science 101
SEPTEMBER 28, 2019
Amazon and Coursera have teamed up to create Getting Started with AWS Machine Learning. Topics covered are: Machine Learning. Computer Vision. NLP. Amazon Sagemaker. Happy Learning!
Analytics Vidhya
SEPTEMBER 4, 2019
Overview What is p-value? Where is it used in data science? And how can we calculate it? We answer all these questions and more. The post Everything you Should Know about p-value from Scratch for Data Science appeared first on Analytics Vidhya.
Speaker: Donna Laquidara-Carr, PhD, LEED AP, Industry Insights Research Director at Dodge Construction Network
In today’s construction market, owners, construction managers, and contractors must navigate increasing challenges, from cost management to project delays. Fortunately, digital tools now offer valuable insights to help mitigate these risks. However, the sheer volume of tools and the complexity of leveraging their data effectively can be daunting. That’s where data-driven construction comes in.
Corinium
SEPTEMBER 18, 2019
Instant noodles and the on-demand life. It’s no secret that, despite the huge movement toward sustainable living, we just can’t live without some things being instant. One such crutch for students worldwide and most of Asia’s young adult population (also the entire American prison system) are the ubiquitous instant noodles. 100 billion servings are eaten every year.
erwin
SEPTEMBER 26, 2019
The benefits of Data Vault automation from the more abstract – like improving data integrity – to the tangible – such as clearly identifiable savings in cost and time. So Seriously … You Should Automate Your Data Vault. By Danny Sandwell. Data Vault is a methodology for architecting and managing data warehouses in complex data environments where new data types and structures are constantly introduced.
O'Reilly on Data
SEPTEMBER 11, 2019
Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena. Strata attracts the leading names in the fields of data management, data engineering, analytics, ML, and artificial intelligence (AI).
KDnuggets
SEPTEMBER 23, 2019
Our list of deep learning researchers and industry leaders are the people you should follow to stay current with this wildly expanding field in AI. From early practitioners and established academics to entrepreneurs and today’s top corporate influencers, this diverse group of individuals is leading the way into tomorrow’s deep learning landscape.
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Entity Resolution Sometimes referred to as data matching or fuzzy matching, entity resolution, is critical for data quality, analytics, graph visualization and AI. Learn what entity resolution is, why it matters, how it works and its benefits. Advanced entity resolution using AI is crucial because it efficiently and easily solves many of today’s data quality and analytics problems.
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