Octopai
JANUARY 8, 2020
To all BI professionals, CIOs, CDOs, and everyone else relying on data to run a business: Happy New Year! It’s going to be…interesting. From California’s new data privacy law going into full effect to potential new U.S. federal data privacy laws on top of an alphabet soup of global laws and regulations, the name of the game for 2020 is going to be “compliance.”.
Analytics Vidhya
JANUARY 14, 2020
Overview Looking to transition into data science? Here are 5 paths for a non-data science person to land a role in this space The. The post 5 Thoughts on How to Transition into Data Science from Different Backgrounds appeared first on Analytics Vidhya.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Corinium
JANUARY 30, 2020
I remember getting excited when it came time for the carnival coming to town. There was always a positivity and goodwill in the air as families brought their little ones to try out the various rides and share a meal. One part you either loved or hated, but were never quite the same after you entered was the “fun” house or “house of horrors”. It was hilarious trying out the different mirrors; Some made you look short and stout, others tall and slim, and then there was the one made your head look
KDnuggets
JANUARY 8, 2020
The standard job description for a Data Scientist has long highlighted skills in R, Python, SQL, and Machine Learning. With the field evolving, these core competencies are no longer enough to stay competitive in the job market.
Advertisement
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have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth.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.
O'Reilly on Data
JANUARY 15, 2020
Roger Magoulas recently sat down with Edward Jezierski, reinforcement learning AI principal program manager at Microsoft, to talk about reinforcement learning (RL). They discuss why RL’s role in AI is so important, challenges of applying RL in a business environment, and how to approach ethical and responsible use questions. Here are some highlights from their conversation: Reinforcement learning is different than simply trying to detect something in an image or extract something from a da
datapine
JANUARY 21, 2020
Big data plays a crucial role in online data analysis , business information, and intelligent reporting. Companies must adjust to the ambiguity of data, and act accordingly. Spreadsheets no longer provide adequate solutions for a serious company looking to accurately analyze and utilize all the business information gathered. That’s where business intelligence reporting comes into play – and, indeed, is proving pivotal in empowering organizations to collect data effectively and transform in
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
Analytics Vidhya
JANUARY 28, 2020
Overview Understand the structure of a Machine Learning Pipeline Build an end-to-end ML pipeline on a real-world data Train a Random Forest Regressor for. The post Build your first Machine Learning pipeline using scikit-learn! appeared first on Analytics Vidhya.
KDnuggets
JANUARY 20, 2020
It’s easy to say "I wanna be a data scientist," but. where do you start? How much time is needed to be desired by companies? Do you need a Master’s degree? Do you need to know every mathematical concept ever derived? The journey might be long, but follow this plan to help you keep moving forward toward your career goal.
Juice Analytics
JANUARY 6, 2020
I like to think that the hero in your data story is your audience. The hero is the person who starts with conflict and, through the narrative journey, is transformed to resolve this conflict. That’s what you want the data story to accomplish for your audience — start with a question and move your audience (hero) to actions that will resolve the question.
Advertisement
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?
datapine
JANUARY 28, 2020
The ability to monitor, visualize, and analyze relevant data gives today’s businesses, across a host of sectors, the power to understand their prospects, make informed decisions, increase efficiencies, and work towards a set of rewarding long term goals. With so much data available to today’s brands and businesses, to extract every drop of value from an ever-growing raft of digital insights and set the kind of KPIs that will drive your venture forward, having an easy to use, a visually-stunning
erwin
JANUARY 9, 2020
Enterprises are trying to manage data chaos. They might have 300 applications, with 50 different databases and a different schema for each one. They also face increasing regulatory pressure because of global data regulations , such as the European Union’s General Data Protection Regulation (GDPR) and the new California Consumer Privacy Act (CCPA), that went into effect last week on Jan. 1.
Analytics Vidhya
JANUARY 5, 2020
Introducing the Learning Path to become a Data Scientist in 2020! Learning paths are easily one of the most popular and in-demand resources we. The post Your Ultimate Learning Path to Become a Data Scientist and Machine Learning Expert in 2020 appeared first on Analytics Vidhya.
Corinium
JANUARY 13, 2020
In the last decade regulatory requirements in financial services increased significantly.
Advertisement
📌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.
KDnuggets
JANUARY 20, 2020
The new algorithm takes a novel approach to neural architecture search.
DataCamp
JANUARY 6, 2020
Understand the differences between the two most popular options for storing big data.
datapine
JANUARY 14, 2020
“There is only one boss. The customer.” – Sam Walton, Walmart’s founder. Customer experience is slowly but surely exceeding both price and product as the world’s most critical brand differentiator, according to numerous articles over the Internet written by industry experts. Brands with the ability to build flawless customer experiences and offer exceptional standards of customer service (CS) stand to set themselves apart from their competitors in a notable way.
erwin
JANUARY 24, 2020
There are three different types of data models: conceptual, logical and physical, and each has a specific purpose. Conceptual Data Models: High-level, static business structures and concepts. Logical Data Models: Entity types, data attributes and relationships between entities. Physical Data Models: The internal schema database design. An organization’s approach to data modeling will be influenced by its particular needs and the goals it is trying to reach, as explained here: What is Data Modeli
Speaker: Mike Rizzo, Founder & CEO, MarketingOps.com and Darrell Alfonso, Director of Marketing Strategy and Operations, Indeed.com
Though rarely in the spotlight, marketing operations are the backbone of the efficiency, scalability, and alignment that define top-performing marketing teams. In this exclusive webinar led by industry visionaries Mike Rizzo and Darrell Alfonso, we’re giving marketing operations the recognition they deserve! We will dive into the 7 P Model —a powerful framework designed to assess and optimize your marketing operations function.
Analytics Vidhya
JANUARY 26, 2020
Overview Regular Expressions or Regex is a versatile tool that every Data Scientist should know about Regex can automate various mundane data processing tasks. The post 4 Applications of Regular Expressions that every Data Scientist should know (with Python code)! appeared first on Analytics Vidhya.
Corinium
JANUARY 30, 2020
Ahead of her presentation at CDAO UK, we spoke with Quantum Metric’s Marina Shapira about predictive analytics, why companies should embrace a culture of experimentation how and CAOs and CXOs can work together effectively. What is behavioural research? And what role should it play in an organization's data and analytics strategy? Behavioural research seeks to understand what motivates people, how they perceive the world, make decisions and form habit.
KDnuggets
JANUARY 17, 2020
This article will tell you about the top 9 mobile apps that help the user in learning and practicing data science and hence is improving their productivity.
DataRobot
JANUARY 27, 2020
In Super Bowl LIV this Sunday, the Kansas City Chiefs will face the San Francisco 49ers in Miami, Florida. This will be the first Super Bowl appearance for the Chiefs in 50 years. After a loss in 2013, the 49ers are looking to secure their sixth Super Bowl ring, which would tie them with the New England Patriots and Pittsburgh Steelers for the league record.
Speaker: Jay Allardyce, Deepak Vittal, Terrence Sheflin, and Mahyar Ghasemali
As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.
datapine
JANUARY 7, 2020
Without big data analytics, companies are blind and deaf, wandering out onto the Web like deer on a freeway. – Geoffrey Moore, Author of Crossing the Chasm & Inside the Tornado. In the digital age, brands, businesses, and organizations have a wealth of information at their fingertips: a level of insight that if leveraged correctly, not only has the power to offer a real competitive edge but provides the potential to innovate, inspire and create a well-oiled commercial machine that continues
erwin
JANUARY 17, 2020
What is Data Modeling? Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise. As the value of data and the way it is used by organizations has changed over the years, so too has data modeling.
Analytics Vidhya
JANUARY 27, 2020
Overview Learn how to perform text classification using PyTorch Understand the key points involved while solving text classification Learn to use Pack Padding feature. The post Build Your First Text Classification model using PyTorch appeared first on Analytics Vidhya.
Corinium
JANUARY 27, 2020
It’s easy to get excited about the many ways AI and advanced analytics will shape the future of healthcare. But the industry has a way to go before these technologies begin having a significant impact on the health of ordinary Americans. In the meantime, there’s a great deal that health organizations can be doing today to deliver better quality care with data.
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.
KDnuggets
JANUARY 16, 2020
With integrations of multiple emerging technologies just in the past year, AI development continues at a fast pace. Following the blueprint of science and technology advancements in 2019, we predict 10 trends we expect to see in 2020 and beyond.
DataRobot
JANUARY 10, 2020
Does your organization apply appropriate human resources governance when hiring staff? Large enterprises tend to follow the same basic processes for hiring human staff. First, hiring managers write a job description, including the tasks the position requires and the skills and attributes of a suitable candidate. Job vacancies are posted, sometimes recruiters are also used, and people submit their resumes for consideration.
Data Science 101
JANUARY 24, 2020
It was an exciting cloud data science week. Lots of interesting stuff to cover, so let’s get started. News. Microsoft DP-100 Certification Updated – The Microsoft Data Scientist certification exam has been updated to cover the latest Azure Machine Learning tools. Google Dataset Search goes GA – search and discover millions of datasets Google Cloud GPU Price Cut – Google reduces the prices of NVIDIA T4 GPUs which should save some money for people doing AI PyTorch 1.4 Relea
Dataiku
JANUARY 31, 2020
Data scientists and business leaders building or using machine learning models and AI systems face a serious challenge today -- how to balance interpretability and accuracy stemming from the difference between black-box and white-box models.
Advertisement
Cloud Development Environments (CDEs) are changing how software teams work by moving development to the cloud. Our Cloud Development Environment Adoption Report gathers insights from 223 developers and business leaders, uncovering key trends in CDE adoption. With 66% of large organizations already using CDEs, these platforms are quickly becoming essential to modern development practices.
Expert insights. Personalized for you.
72 
Let's personalize your content