Analytics (106)

• Data Warehousing with Snowflake for Beginners - Feb 3, 2022.
  
  This tutorial provides only a brief synopsis of the data warehouse in Snowflake, which we will go through in more detail.

  Analytics

• Cutting Down Implementation Time by Integrating Jupyter and KNIME - Dec 23, 2021.
  
  Are you a KNIME fan or a Jupyter fan? Well, here you don’t have to choose.

  Analytics, Data Science, Jupyter, Knime

• A Faster Way to Prepare Time-Series Data with the AI & Analytics Engine - Dec 20, 2021.
  
  Many real-world datasets consist of records of events that occur at arbitrary and irregular intervals. These datasets then need to be processed into regular time series for further analysis. We will use the AI & Analytics Engine to illustrate how you can prepare your time-series data in just 1 step.

  AI, Analytics, Time Series

• Data Science & Analytics Industry Main Developments in 2021 and Key Trends for 2022 - Dec 14, 2021.
  
  We have solicited insights from experts at industry-leading companies, asking: "What were the main AI, Data Science, Machine Learning Developments in 2021 and what key trends do you expect in 2022?" Read their opinions here.

  2022 Predictions, AI, Analytics, Cloud, Data Lake, Data Science, Data Warehouse, Deep Learning, Machine Learning, Synthetic Data

• AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2021 and Key Trends for 2022 - Dec 8, 2021.
  
  2021 has almost come and gone. We saw some standout advancements in AI, Analytics, Machine Learning, Data Science, Deep Learning Research this past year, and the future, starting with 2022, looks bright. As per KDnuggets tradition, our collection of experts have contributed their insights on the matter. Read on to find out more.

  2022 Predictions, AI, Analytics, Data Science, Deep Learning, Machine Learning

• How Data Scientists Can Get the Ear of CFOs (And Why You Want It) - Dec 8, 2021.
  
  Hey, data scientists! Here’s how to bend your CFO’s ear, equip your company with high-quality analysis, and boost your value and career in the process.

  Analytics, Career Advice, Data Scientist

• Two Simple Things You Need to Steal from Agile for Data and Analytics Work - Nov 16, 2021.
  
  Peer Review and Definition of Done: small changes, BIG impact.

  Agile, Analytics, Data Science, Data.world

• What’s missing from self-serve BI and what we can do about it - Nov 11, 2021.
  
  The notion of self-service BI tools caught an expectation that they could provide a magic formula for easily helping everyone understand all the data. But, such an end-result isn't occurring in practice. To identify a better approach, we need to take a step back and determine what problem is actually trying to be solved.

  Advice, Analytics, BI, Self-service

• Is the Modern Data Stack Leaving You Behind? - Nov 1, 2021.
  
  The modern data stack narrative is largely dominated by analytics engineering. Where does that leave data engineers? Discover the difference between the MDS for data engineers & analytics engineers.

  Analytics, Data Engineer, Data Engineering, Tools

• DATAnalyze 2021 Analytics Hackathon Sponsored by Microsoft and WorldData.AI, $125,000 in prizes! - Oct 21, 2021.
  
  Tech Tree Root is excited to introduce you to our DATAnalyze 2021 sponsors Microsoft, WorldData.AI, and HBCU Connect! Our online analytics hackathon is offering up to $125,000 USD in prizes!

  Analytics, Hackathon, Microsoft, WorldData.AI

• How to Create an Interactive Dashboard in Three Steps with KNIME Analytics Platform - Oct 19, 2021.
  
  In this blog post I will show you how to build a simple, but useful and good-looking dashboard to present your data - in three simple steps!

  Analytics, Dashboard, Data Visualization, Knime, Platform

• How I Built A Perfect Model And Got Into Trouble - Oct 12, 2021.
  
  Data-driven decisions, actionable insights, business impact—you've seen these buzzwords in data science jobs descriptions. But, just focusing on these terms doesn't automatically lead to the best results. Learn from this real-world scenario that followed data-driven indecisiveness, found misleading insights, and initially created a negative business impact.

  Analytics, Business, Customer Analytics, Finance, KPI, Metrics

• Data Science Process Lifecycle - Sep 29, 2021.
  
  How would it feel to know that without a doubt, the data projects you were working on would create TRUE ROI for your organization? Stick around until the end to get my data science process lifecycle framework so that each data project you run is a smashing success.

  Analytics, Data Science, Data Scientist, Workflow

• How causal inference lifts augmented analytics beyond flatland - Aug 27, 2021.
  
  In our quest to better understand and predict business outcomes, traditional predictive modeling tends to fall flat. However, causal inference techniques along with business analytics approaches can unravel what truly changes your KPIs.

  Analytics, Causality, Data Science, Python, Regression

• Using Twitter to Understand Pizza Delivery Apprehension During COVID - Aug 6, 2021.
  
  Analyzing customer sentiments and capturing any specific difference in emotion to order Dominos pizza in India during lockdown.

  Analytics, COVID-19, Data Science, Retail, Sentiment Analysis, Twitter

• How To 2x Your Data Analytics Consulting Rates (Overnight) - Aug 3, 2021.
  
  Looking to up your data analytics consulting rates? Learn exactly what most freelancers are charging, and the rates you SHOULD be charging as a business intelligence and analytics consultant. This post will show you what you need to know to achieve maximum results for your data consulting career.

  Analytics, Career Advice, Careers, Data Science

• In-Warehouse Machine Learning and the Modern Data Science Stack - Jun 24, 2021.
  
  As your organization matures its data science portfolio and capabilities, establishing a modern data stack is vital to enabling such growth. Here, we overview various in-data warehouse machine learning services, and discuss each of their benefits and requirements.

  Amazon Redshift, Analytics, BigQuery, Cloud, Data Science, Data Warehouse, Machine Learning, Modern Data Stack

• Create and Deploy Dashboards using Voila and Saturn Cloud - Jun 23, 2021.
  
  Working with and training large datasets, maintaining them all in one place, and deploying them to production is a challenging job. In this article, we covered what Saturn Cloud is and how it can speed up your end-to-end pipeline, how to create dashboards using Voila and Python and publish them to production in just a few easy steps.

  Analytics, Cloud, Dashboard, Data Science, Machine Learning, Python

• Analytics Engineering Everywhere - Jun 22, 2021.
  
  Many new roles have appeared in the data world ever since the rise of the Data Scientist took the spotlight several years ago. Now, there is a new core player ready to take center stage, and we may see in five years, nearly every organization will have an Analytics Engineering team.

  Analytics, Analytics Engineering, Data Engineering, dbt

• What is Segmentation? - Jun 22, 2021.
  
  Segmentation refers to many things, and is one of the most frequently used words in marketing This article looks at segmentation from a somewhat different-than-usual perspective.

  Analytics, Marketing Analytics, Segmentation

• SAS® Visual Data Science Decisioning powered by SAS® Viya®: Free Trial - Jun 8, 2021.
  
  SAS® Visual Data Science Decisioning provides the ultimate analytics experience. Start your free trial and get access to the latest in data visualization, machine learning, forecasting, model deployment and more.

  Analytics, Data Science, Data Visualization, Decision Support, SAS, Viya

• 5 Tips for Picking an Edge AI Platform - Jun 8, 2021.
  
  Edge Analytics isn’t just coding and tools. The different environment outside the datacenter or cloud means a purpose built platform is the best way to deliver consistent results. We discuss 5 different considerations for an edge platform to support your training and deployment.

  AI, Analytics, Platform

• Where Did You Apply Analytics, Data Science, Machine Learning in 2020/2021? - May 25, 2021.
  
  Take part in the latest KDnuggets survey, and let us know where you have been applying Analytics, Data Science, Machine Learning in 2020/2021.

  Analytics, Data Science, Machine Learning, Poll, Survey

• Best Python Books for Beginners and Advanced Programmers - May 14, 2021.
  
  Let's take a look at nine of the best Python books for both beginners and advanced programmers, covering topics such as data science, machine learning, deep learning, NLP, and more.

  Analytics, Books, Data Science, Deep Learning, Machine Learning, Python

• Make Connections With SAS Live Web Learning - May 11, 2021.
  
  Through a year of uncertainty, the demand for analytics skills and the desire to continue skills development remained consistent. Take this opportunity to join SAS expert instructors and learn the latest skills in a Live Web class.

  Analytics, Credit Risk, Data Science Education, Online Education, SAS

• Top 3 Challenges for Data & Analytics Leaders - Apr 26, 2021.
  
  The author shares the 3 top challenges faced as they led and established a data & analytics function, as well as ways in which these challenges were addressed. How have you solved the one challenge which has remained elusive to the author?

  Analytics, Challenges, Data Analytics, Data Leadership

• People Skills for Analytical Thinkers - Feb 19, 2021.
  
  Research shows that people skills are becoming more important with the rise of AI. A great way to boost these skills is by reading the new book: People Skills for Analytical Thinkers.

  Analytics, Book, Communication, Data Science, Data Science Skills

• Forecasting Stories 5: The story of the launch - Feb 18, 2021.
  
  New products forecasting can be very difficult - there is no history to start with, and hence no base line. The number of assumptions can be huge. The best way to forecast then, is to try parallel approaches, build different views and triangulate on a common range.

  Analytics, Business, Forecasting

• Where is Marketing Data Science Headed? - Jan 5, 2021.
  
  Marketing data science - data science related to marketing - is now a significant part of marketing. Some of it directly competes with traditional marketing research and many marketing researchers may wonder what the future holds in store for it.

  Analytics, Data Science, Marketing

• AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2020 and Key Trends for 2021 - Dec 3, 2020.
  
  2020 is finally coming to a close. While likely not to register as anyone's favorite year, 2020 did have some noteworthy advancements in our field, and 2021 promises some important key trends to look forward to. As has become a year-end tradition, our collection of experts have once again contributed their thoughts. Read on to find out more.

  2021 Predictions, AI, Ajit Jaokar, Analytics, Brandon Rohrer, Daniel Tunkelang, Data Science, Deep Learning, Machine Learning, Pedro Domingos, Predictions, Research, Rosaria Silipo

• Introduction to Data Engineering - Dec 3, 2020.
  
  The Q&A for the most frequently asked questions about Data Engineering: What does a data engineer do? What is a data pipeline? What is a data warehouse? How is a data engineer different from a data scientist? What skills and programming languages do you need to learn to become a data engineer?

  Analytics, Data Engineer, Data Engineering, Data Science, Skills

• How to Effectively Obtain Consumer Insights in a Data Overload Era - Sep 17, 2020.
  
  Everybody knows how important is understanding your customer, but how to do that in an era of Information Overload?

  Analytics, Customer Analytics, Data Science

• 9 Developing Data Science & Analytics Job Trends - Sep 7, 2020.
  
  With so much disruption in 2020 already, a recent report by Burtch Works looks ahead to next year and beyond, and shares insights about how today's hiring market trends may impact our work lives for years to come.

  Analytics, Burtch Works, Career, COVID-19, Data Science, Jobs, Trends

• Data is everywhere and it powers everything we do! - Aug 28, 2020.
  
  In this article I would like to focus on how companies can start their data-centric strategies and how to achieve success in their data transformation journeys. Have tried to share my thoughts why companies have to consider data at its epitome for their growth, for being competitive, for being smarter, innovative and be prepared for any unforeseen market surprises.

  Analytics, Business, Data Science

• 5 Big Trends in Data Analytics - Jul 30, 2020.
  
  Data analytics is the process by which data is deconstructed and examined for useful patterns and trends. Here we explore five trends making data analytics even more useful.

  Analytics, Blockchain, Data Analytics, NLP, Trends

• Appropriately Handling Missing Values for Statistical Modelling and Prediction - May 22, 2020.
  
  Many statisticians in industry agree that blindly imputing the missing values in your dataset is a dangerous move and should be avoided without first understanding why the data is missing in the first place.

  Advice, Analytics, Business Analytics, Data Preparation, Data Science, Data Scientist, Missing Values, Statistics

• Passive Data Collection and Actionable Results: What to Know - Feb 21, 2020.
  
  There are plenty of ways to get actionable results by using passive data. However, such an outcome will not happen without careful forethought. Data analysts must consider several crucial specifics, including what questions they want and expect the information to answer, and how they'll apply the findings to aid the business.

  Analytics, Customer Analytics, Data Curation, Datasets

• How HR Is Using Data Science and Analytics to Close the Gender Gap - Jan 3, 2020.
  
  The gender gap can extend to the lack of equal representation in certain industries or career paths, and there's an extraordinarily long way to go before people will be on equal footing in the labor market. Human resources professionals can rely on data analytics to make progress.

  Analytics, Data Science, Gender, HR

• AI, Analytics, Machine Learning, Data Science, Deep Learning Technology Main Developments in 2019 and Key Trends for 2020 - Dec 11, 2019.
  
  We asked leading experts - what are the most important developments of 2019 and 2020 key trends in AI, Analytics, Machine Learning, Data Science, and Deep Learning? This blog focuses mainly on technology and deployment.

  2020 Predictions, AI, Analytics, Bill Schmarzo, Carla Gentry, Data Science, Doug Laney, Jen Underwood, Kate Strachnyi, Machine Learning, Meta Brown, Ronald van Loon, Tom Davenport, Trends

• Intro to Grafana: Installation, Configuration, and Building the First Dashboard - Dec 10, 2019.
  
  One of the biggest highlights of Grafana is the ability to bring several data sources together in one dashboard with adding rows that will host individual panels. Let's look at installing, configuring, and creating our first dashboard using Grafana.

  Analytics, BI, Business Analytics, Dashboard

• AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2019 and Key Trends for 2020 - Dec 9, 2019.
  
  As we say goodbye to one year and look forward to another, KDnuggets has once again solicited opinions from numerous research & technology experts as to the most important developments of 2019 and their 2020 key trend predictions.

  2020 Predictions, AI, Ajit Jaokar, Analytics, Andriy Burkov, Anima Anandkumar, Daniel Tunkelang, Data Science, Deep Learning, Machine Learning, Pedro Domingos, Research, Rosaria Silipo, Xavier Amatriain

• How Data Analytics Can Assist in Fraud Detection - Nov 11, 2019.
  
  A primary advantage of data analytics tools is that they can handle massive quantities of information at once. These solutions typically learn what's normal within a collection of information and how to spot anomalies.

  Analytics, Fraud, Fraud Detection

• An Eight-Step Checklist for An Analytics Project - Nov 6, 2019.
  
  Follow these eight headings of an audit sheet that business analysts should address before submitting the results of their analytics project. One recommended approach is to rewrite each step as a question, answer it, and then attach it to your project.

  Analytics, Checklist, Deployment, Feature Selection, Statistics

• Four questions to help accurately scope analytics engineering project - Oct 9, 2019.
  
  Being really good at scoping analytics projects is crucial for team productivity and profitability. You can consistently deliver on time if you work out the issue first, and these four questions can help you prepare.

  Analytics, Data Engineering, dbt, Deployment

• The Future of Analytics and Data Science - Sep 26, 2019.
  
  Learn about the current and future issues of data science and possible solutions from this interview with IADSS Co-founder, Dr. Usama Fayyad following his keynote speech at ODSC Boston 2019.

  Analytics, IADSS, Kate Strachnyi, ODSC, Trends, Usama Fayyad

• How Bad is Multicollinearity? - Sep 17, 2019.
  
  For some people anything below 60% is acceptable and for certain others, even a correlation of 30% to 40% is considered too high because it one variable may just end up exaggerating the performance of the model or completely messing up parameter estimates.

  Analytics, Multicollinearity, Regression, Statistics

• What’s the difference between analytics and statistics? - Sep 6, 2019.
  
  From asking the best questions about data to answering those questions with certainty, understanding the value of these two seemingly different professions is clarified when you see how they should work together.

  Analytics, Explained, Statistics

• Emoji Analytics - Aug 30, 2019.
  
  Emoji is becoming a global language understandable by anyone who expresses... emotion. With the pervasiveness of these little Unicode blocks, we can perform analytics on their use throughout social media to gain insight into sentiments around the world.

  Analytics, Emoji, Social Network Analysis, Twitter

• Lagrange multipliers with visualizations and code - Aug 6, 2019.
  
  In this story, we’re going to take an aerial tour of optimization with Lagrange multipliers. When do we need them? Whenever we have an optimization problem with constraints.

  Analytics, Mathematics, Optimization, Python

• Ten more random useful things in R you may not know about - Jul 31, 2019.
  
  I had a feeling that R has developed as a language to such a degree that many of us are using it now in completely different ways. This means that there are likely to be numerous tricks, packages, functions, etc that each of us use, but that others are completely unaware of, and would find useful if they knew about them.

  Advice, Analytics, Data Science, R

• Top 10 Best Podcasts on AI, Analytics, Data Science, Machine Learning - Jul 29, 2019.
  
  Check out our latest Top 10 Most Popular Data Science and Machine Learning podcasts available on iTunes. Stay up to date in the field with these recent episodes and join in with the current data conversations.

  AI, Analytics, Data Science, Machine Learning, Podcast

• Big Data for Insurance - Jul 18, 2019.
  
  The insurance industry has always been quite conservative; however, the adoption of new technologies is not just a modern trend but a necessity to maintain the competitive pace. In the modern digital era, Big Data technologies help to process vast amounts of information, increase workflow efficiency, and reduce operational costs. Learn more about the benefits of Big Data for insurance from our material.

  Analytics, Big Data, Insurance, Predictive Analytics

• Ten random useful things in R that you might not know about - Jun 20, 2019.
  
  Because the R ecosystem is so rich and constantly growing, people can often miss out on knowing about something that can really help them in a task that they have to complete

  Advice, Analytics, Data Science, R

• Sisense BloX – Go Beyond Dashboards - Apr 18, 2019.
  
  Introducing Sisense BloX, the tool that allows you to integrate your business platforms inside your dashboards using prebuilt templates. Users stay within the dashboard environment and go from understanding insights to taking action—in one click.

  Analytics, Dashboard, Sisense

• The Four Levels of Analytics Maturity - Mar 26, 2019.
  
  We outline our four-step model to categorize how successfully a company uses analytics by its ability to show the analytics, uncover underlying trends, and take action based on them.

  Analytics, Business, Deployment, Performance, Visualization

• How to Capture Data to Make Business Impact - Mar 21, 2019.
  
  We take a look at the formula for calculating the efficiency of a data capturing method, before going onto explain the concept of Smart Data.

  Analytics, Big Data, Data Science, ROI, Smart Data

• The Analytics Engineer – new role in the data team - Feb 13, 2019.
  
  In a constantly changing landscape and with many companies, the roles and responsibilities of data engineers, analysts, and data scientists are changing, forcing the introduction of a new role: The Analytics Engineer.

  Analytics, Analytics Team, Data Science Team, Engineer, Skills

• The Essential Data Science Venn Diagram - Feb 4, 2019.
  
  A deeper examination of the interdisciplinary interplay involved in data science, focusing on automation, validity and intuition.

  Analytics, Data Science, Machine Learning, Statistics, Venn Diagram

• Top Active Blogs on AI, Analytics, Big Data, Data Science, Machine Learning – updated - Jan 14, 2019.
  
  Stay up-to-date with the latest technological advancements using our extensive list of active blogs; this is a list of 100 recently active blogs on Big Data, Data Science, Data Mining, Machine Learning, and Artificial intelligence.

  AI, Analytics, Big Data, Blogs, Data Mining, Data Science, Data Visualization, Machine Learning

• Industry Predictions: AI, Machine Learning, Analytics & Data Science Main Developments in 2018 and Key Trends for 2019 - Dec 18, 2018.
  
  This is a collection of data science, machine learning, analytics, and AI predictions for next year from a number of top industry organizations. See what the insiders feel is on the horizon for 2019!

  2019 Predictions, AI, Analytics, Data Science, Domino, dotData, Figure Eight, Industry, Knime, Machine Learning, MapR, MathWorks, OpenText, ParallelM, Salesforce, Splice Machine, Splunk

• Self-Service Analytics and Operationalization – Why You Need Both - Nov 12, 2018.
  
  Get the guidebook / whitepaper for a look at how today's top data-driven companies scale their advanced analytics & machine learning efforts.

  Analytics, Data Science, Dataiku, Deployment, Self-service

• Healthcare Analytics Made Simple - Nov 12, 2018.
  
  Finally, a book on Python healthcare machine learning techniques is here! Healthcare Analytics Made Simple does just what the title says: it makes healthcare data science simple and approachable for everyone.

  Analytics, Book, Healthcare, Pandas, Python

• Introducing Path Analysis Using R - Sep 27, 2018.
  
  Path analysis is an extension of multiple regression. It allows for the analysis of more complicated models.

  Analysis, Analytics, R

• Interpreting a data set, beginning to end - Aug 20, 2018.
  
  Detailed knowledge of your data is key to understanding it! We review several important methods that to understand the data, including summary statistics with visualization, embedding methods like PCA and t-SNE, and Topological Data Analysis.

  Analytics, Big Data, Data Science, Data Visualization, Machine Learning, SAS, Statistics, t-SNE

• 5 of Our Favorite Free Visualization Tools - Jul 5, 2018.
  
  5 key free data visualization tools that can provide flexible and effective data presentation.

  Analytics, D3.js, Data Science, Data Visualization, Free Software, R, Tableau

• Why the Data Lake Matters - Jun 22, 2018.
  
  This post outlines why the data lake matters, outlining the complexity of a data lake and taking a look at its evolution over time.

  Analytics, Data, Data Lakes

• YouTube videos on database management, SQL, Datawarehousing, Business Intelligence, OLAP, Big Data, NoSQL databases, data quality, data governance and Analytics – free - May 18, 2018.
  
  Watch over 20 hours of YouTube videos on databases and database design, Physical Data Storage, Transaction Management and Database Access, and Data Warehousing, Data Governance and (Big) Data Analytics - all free.

  Analytics, Bart Baesens, Big Data, Business Intelligence, Data Governance, Data Quality, Data Warehousing, Databases, NoSQL, SQL, Youtube

• Principles of Guided Analytics - Mar 27, 2018.
  
  KNIME outline their guided analytics system and explain how this can assist data scientists to predict future outcomes.

  Analytics, Data Preparation, Knime, Michael Berthold, Workflow

• New Book: Credit risk analytics, The R Companion - Mar 16, 2018.
  
  Credit risk analytics in R will enable you to build credit risk models from start to finish, with access to real credit data on accompanying website, you will master a wide range of applications.

  Analytics, Bart Baesens, Credit Risk, R

• Web Scraping with Python: Illustration with CIA World Factbook - Mar 16, 2018.
  
  In this article, we show how to use Python libraries and HTML parsing to extract useful information from a website and answer some important analytics questions afterwards.

  Analytics, CIA, Python, Web Scraping

• Upcoming Meetings in AI, Analytics, Big Data, Data Science, Deep Learning, Machine Learning: February and Beyond - Feb 2, 2018.
  
  Coming soon: TDWI Las Vegas, BI + Analytics Huntington Beach, Strata San Jose, IBM Think Las Vegas, Big Data & Analytics Singapore, KNIME Berlin, Nvidia GPU, and more.

  AI, Analytics, Big Data, Las Vegas, London, Meetings

• How to build a Successful Advanced Analytics Department - Jan 4, 2018.
  
  This article presents our opinions and suggestions on how an Advanced Analytics department should operate. We hope this will be useful for those who want to implement analytics work in their company, as well as for existing departments.

  Pages: 1 2

  Analytics, Analytics Team, Business, Data Science Team, Gartner, KPI

• A Guide for Customer Retention Analysis with SQL - Dec 19, 2017.
  
  Customer retention curves are essential to any business looking to understand its clients, and will go a long way towards explaining other things like sales figures or the impact of marketing initiatives. They are an easy way to visualize a key interaction between customers and the business.

  Pages: 1 2

  Analytics, Customer Analytics, SQL, Statsbot

• Edge Analytics – What, Why, When, Who, Where, How? - Oct 11, 2017.
  
  Edge analytics is the collection, processing, and analysis of data at the edge of a network either at or close to a sensor, a network switch or some other connected device.

  Analytics, Edge Analytics, IoT, Sensors

• Big Data Architecture: A Complete and Detailed Overview - Sep 19, 2017.
  
  Data scientists may not be as educated or experienced in computer science, programming concepts, devops, site reliability engineering, non-functional requirements, software solution infrastructure, or general software architecture as compared to well-trained or experienced software architects and engineers.

  Analytics, Big Data, Big Data Architecture, Cloud, Cloud Computing, Scalability, Software, Software Engineering

• Closing the Insights-to-Action Gap - Sep 5, 2017.
  
  There are many types of analytics for getting insight out of data, but the bigger and more difficult challenge is turning that insight into action. What should we do differently based on your findings?

  Analytics, Gartner, Optimization, Skills

• Google Analytics Audit Checklist and Tools - Aug 9, 2017.
  
  In this post, a Google Analytics & Google AdWords expert shares his tips and tools of intelligent Google Analytics auditing. Read on for some practical insight.

  Analytics, Checklist, Google Analytics, Web Analytics

• Why Apache Arrow is the future for open source-columnar memory analytics - Aug 7, 2017.
  
  Apache Arrow is a de-facto standard for columnar in-memory analytics. In the coming years we can expect all the big data platforms adopting Apache Arrow as its columnar in-memory layer.

  Analytics, Apache, Apache Arrow, Big Data, In-Memory Computing, Open Source

• The Key to Data Monetization - Jul 31, 2017.
  
  While I have talked frequently about the concept of Analytic Profiles, I’ve never written a blog that details how Analytic Profiles work. So let’s create a “Day in the Life” of an Analytic Profile to explain how an Analytic Profile works to capture and “monetize” your analytic assets.

  Analytics, Data Monetization, Data Science, Monetizing

• Marketing Analytics for Data Rich Environments - Jul 14, 2017.
  
  A lot is changing in the world of marketing analytics. Marketing scientist Kevin Gray asks Professor Michel Wedel, a leading authority on this topic from the Robert H. Smith School of Business at the University of Maryland, what marketing researchers and data scientists most need to know about it.

  Analytics, Big Data, Marketing Analytics

• The 4 Types of Data Analytics - Jul 13, 2017.
  
  We focus on the four types of data analytics we encounter in data science: Descriptive, Diagnostic, Predictive and Prescriptive.
   
   

  Analytics, Descriptive Analytics, Hans Rosling, Predictive Analytics, Prescriptive Analytics

• The Analytics of Emotion and Depression - Apr 26, 2017.
  
  Analytics can be used to provide a boost to the cure of depression. How analytics is being adopted by companies like Microsoft, Facebook to handle and detect vulnerable targets of depression.

  Analytics, Depression, India, Instagram, Sentiment Analysis, Social Media Analytics, Text Analysis

• Career Advice for Analytics & Data Science Professionals - Feb 13, 2017.
  
  In our experience working with many quantitative professionals over the years, the two main areas that contribute to long-term career growth are networking and continuous learning. Here is specific advice on how to do this and tips for Continuous Learning.

  Advice, Analytics, Burtch Works, Career, Data Science, Hiring

• An ode to the analytics grease monkeys - Feb 2, 2017.
  
  Analytics is not one time job. It needs to be automated, deployed and improved for future business analytics requirements. Here an IBM expert discusses about development & deployment of analytics assets and capabilities of it.

  Analytics, Analytics Leader, CRISP-DM, Deployment, IBM, IBM DSX, ROI

• Fixing Deployment and Iteration Problems in CRISP-DM - Feb 1, 2017.
  
  Many analytic models are not deployed effectively into production while others are not maintained or updated. Applying decision modeling and decision management technology within CRISP-DM addresses this.

  Analytics, CRISP-DM, Data Mining, Data Science, Decision Modeling, IIA, Methodology

• Text Mining Amazon Mobile Phone Reviews: Interesting Insights - Jan 10, 2017.
  
  We analyzed more than 400 thousand reviews of unlocked mobile phones sold on Amazon.com to find out insights with respect to reviews, ratings, price and their relationships.

  Amazon, Analytics, Product reviews, Sentiment Analysis, Text Analytics, Text Mining

• A Reference Architecture for Self-Service Analytics - Nov 10, 2016.
  
  The keys to self-service analytics success are organizational. In addition to a governed self-service architecture, companies need to establish governance committees and gateways, create federated organizations with co-located BI developers, and provide continuous education, training, and support. Learn how to do this in this report.

  Analytics, Architecture, Self-service

• Do You Suffer From Analytic Personality Disorder (APD)? - Nov 2, 2016.
  
  Read this lighthearted take on Analytics Personality Disorder, a (nonexistent) syndrome for those obsessed with analytics.

  Analytics, Humor, Psychology, Society

• Embedded Analytics: The Future of Business Intelligence - Sep 30, 2016.
  
  An overview of the evolution of Business Intelligence, and some insight into where its future lie: embedded analytics.

  Analytics, API, Business Intelligence

• Introducing Dask for Parallel Programming: An Interview with Project Lead Developer - Sep 7, 2016.
  
  Introducing Dask, a flexible parallel computing library for analytics. Learn more about this project built with interactive data science in mind in an interview with its lead developer.

  Analytics, Continuum Analytics, Dask, Data Science, Distributed Computing, Parallelism, Python, Scientific Computing

• The Evolution of IoT Edge Analytics: Strategies of Leading Players - Sep 2, 2016.
  
  This article explores the significance and evolution of IoT edge analytics. Since the author believes that hardware capabilities will converge for large vendors, IoT analytics will be the key differentiator.

  Analytics, Cisco, Dell, HPE, IBM, Intel, IoT, PMML

• Data Science of Reviews: ReviewMeta tool Automatically Detects Unnatural Reviews on Amazon - Aug 23, 2016.
  
  ReviewMeta is a tool that analyzes millions of reviews and helps customers decide which ones to trust. As the dataset grows, so do the insights on unbiased reviews.

  Amazon, Analytics, Customer Analytics, Data Mining, Trends

• Build vs Buy – Analytics Dashboards - Jul 29, 2016.
  
  Read this post on choosing between available analytics dashboard options, and designing your own. Get an informed opinion.

  Analytics, Dashboard

• The Big Data Ecosystem is Too Damn Big - Jun 28, 2016.
  
  The Big Data ecosystem is just too damn big! It's complex, redundant, and confusing. There are too many layers in the technology stack, too many standards, and too many engines. Vendors? Too many. What is the user to do?

  Analytics, Big Data, Business Analytics

• Thinking About Analytics Readiness - Jun 16, 2016.
  
  This article touches upon an important but under-discussed topic of analytics readiness, including whether and when organizations should engage in analytics.

  Analytics, Analytics Strategy, Culture, Strategy

• 5 Ways in Which Big Data Can Help Leverage Customer Data - May 25, 2016.
  
  Every business enterprise realizes the importance of big data but rarely puts the customer data that they possess to good use. Here are few ways enterprises can leverage customer data.

  Analytics, Big Data, Data Management, Data Mining

• Tips for Data Scientists: Think Like a Business Executive - May 18, 2016.
  
  Thinking like a Data Scientist is important; it puts businesses and business leaders in an analytical frame of mind. But it is also important for Data Scientists to be able to think like business executives. Read on to find out why.

  Advice, Analytics, Data Scientist

• How Much do Analytics Salaries Increase when Changing Jobs? - May 4, 2016.
  
  A data-informed analysis of analytics career salaries and their increase when changing jobs.

  Analytics, Burtch Works, Career, Salary

• Data Scientist Survey: What Is An Interesting Result? - Apr 28, 2016.
  
  A survey requesting feedback from data scientists on their opinion of what an interesting result is. The survey is anonymous, has only a single mandatory question, and takes only 5 minutes.

  Analytics, Survey

• Advantages and Risks of Self-Service Analytics - Apr 13, 2016.
  
  Self-service analytics is likely to spread in all the business layers, and with proper care to avoid certain risks, the culture of self-service analytics will help all organizations.

  Analytics, Citizen Data Scientist, Gartner, Risks, Self-service

• How Long Should You Stay at Your Analytics Job? - Aug 7, 2015.
  
  Considering the huge demand for the data scientists many are pondering to switch for a better profile and salary. But, there some things to be pondered about like what should be the interval between two switches, acquiring new skills and your loyalty.

  Analytics, Burtch Works, Data Scientist, Hiring

• Interview: Brad Klingenberg, StitchFix on Building Analytics-powered Personal Stylist - Mar 20, 2015.
  
  We discuss StitchFix, how it leverages Analytics, understanding customer preferences, and pros-and-cons of involving human judgement in the recommendation process.

  Analytics, Brad Klingenberg, Customer Experience, Recommendations, Stitch Fix

• Interview: Vince Darley, King.com on the Serious Analytics behind Casual Gaming - Mar 18, 2015.
  
  We discuss key characteristics of social gaming data, ML use cases at King, infrastructure challenges, major problems with A-B testing and recommendations to resolve them.

  A/B Testing, Analytics, Gaming, Infrastructure, King.com, Machine Learning, Predictive Analysis, Vince Darley

• Interview: Paul Robbins, STATS on the Potential and Challenges for Sports Analytics - Jan 5, 2015.
  
  We discuss Analytics at STATS, typical daily tasks, ICE Analytics platform, key challenges, response from coaches/players, career advice and more.

  Analytics, Challenges, Coaching, NBA, Paul Robbins, Performance, Sports, STATS

• Interview: Brian Hampton, San Francisco 49ers on Playing Football the Analytics Way - Dec 19, 2014.
  
  We discuss the role of analytics in football, the underrated challenges, evolution since the era of draft trade value chart and analytics-supported team selection.

  Analytics, Brian Hampton, Challenges, Coaching, Competition, Football, NFL, Sports, Team

• Hiring Data Scientists: What to look for? - Sep 9, 2014.
  
  Know key characteristics of what makes up a good data scientist based upon the three authors’ consulting and research experience, having collaborated with many companies world-wide on the topics of big data and analytics.

  Analytics, Big Data, Business, Data Mining, Data Scientist, Hiring, Programming, Skills, Statistics