It is sometimes said that you don't need to know math to be a data scientist. Sometimes the opposite is said, after all, data science is supposed to be a science! Regardless, below are a few of my articles featuring how data science and math can benefit from each other - not just math to solve data science problems, but also data science to solve math problems.
Having spent the better part of the last decade helping organisations in the U.S. and the U.K. use data to drive profit, efficiency, and performance improvements, I thought it would be helpful to jot down best practices for organizations that are looking to get the most value out of their enterprise-level financial and operational data sets.
Every organisation entering the roaring 20s knows that they must use their data as a strategic differentiator to gain a competitive advantage and…Continue
Added by Fahad Zaidi on January 19, 2020 at 6:00am — No Comments
Imagine this scenario:
You enter your dentist’s office as a follow-up visit to the 6-month checkup you had last week. You’re nervous because the checkup revealed bleeding in your gums and cracks in your fillings, all things that require your dentist’s repair on this occasion.
So, you’re there nervously fidgeting in the lobby waiting for your name to be called, envisioning all sorts of dentistry implements of torture that will soon be…Continue
Added by Bill Schmarzo on January 17, 2020 at 12:30pm — No Comments
Quantum computers come in 2 varieties, quantum annealers and quantum gate models. So far, DWave is the only company selling quantum annealers.
A third type of device is now available from Fujitsu. Fujitsu calls its device a "quantum inspired digital annealer". The Fujitsu device does not have any quantum correlation (quantum entanglement)…Continue
Added by Robert R. Tucci on January 16, 2020 at 1:30pm — No Comments
Data Science is an increasingly competitive field and participants are constantly working hard to build more levels of skill and experience. This trend has given rise to ever more demanding job descriptions for the position. To stay competitive, it makes sense to prepare yourself for new ways of working coupled with a variety of new tools. In an attempt to combat the “unicorn” mentality where many firms try to hire a single individual to fill roles for data scientist, data engineer,…Continue
Added by ODSC on January 16, 2020 at 1:00pm — No Comments
This is a major contribution of analytics and big data when you talk about the success of mobile app development. Big Data is large data sets that can be analyzed to know more about the user’s interests, demographics, trends and interactions. We rely on mobile apps present on our phone for most of the tasks like a reminder, planner, health and fitness, etc.…Continue
Summary: This blog details R data.table programming to handle multi-gigabyte data. It shows how the data can be efficiently loaded, "normalized", and counted. Readers can readily copy and enhance the code below for their own analytic needs. An intermediate level of R coding sophistication is assumed.
In my travels over the holidays, I…Continue
Added by steve miller on January 15, 2020 at 5:29am — No Comments
One of the main requirements for modern information systems is the high data processing rate. Among the solutions to solve this problem the popular one is to use high-performance databases. This article will review and compare two popular databases in performance terms:…Continue
Added by Igor Bobriakov on January 10, 2020 at 12:12am — No Comments
Business Intelligence (BI) and Business Analytics (BA) are both used to interpret business information and create data-based action plans. The two terms are frequently used interchangeably, and many people consider one to be a subset of the other (there's some disagreement about whether BI is a subset of BA, or BA is a subset of BI). However, it might be more accurate to describe them as two arms of successful business planning: BI tells you the…Continue
Countless hours of online courses haven’t prepared me for challenges in my first full-time position as a data scientist. Yes, I learned Python well enough to land the job, but the reality of developing a data science project went beyond my anticipations. Now it’s time for me to pinpoint several misconceptions and matters that are not voiced enough.
Added by Tomasz Szmidt on January 5, 2020 at 3:03am — No Comments
Data scientists are disappearing. No, not in the physical sense (no rapture here), but in the job market. The term “data science” has been a catch-all term for years, but as companies better learn what goes into hiring data science teams, the generic “data science” job titles might go the way of the dodo.
Not that we’re sad about it. Confusing job postings and a misunderstanding of the fundamentals of working in data science has led to disillusionment on both sides.…Continue
Added by ODSC on January 3, 2020 at 7:00am — No Comments
Bayesian inference is the re-allocation of credibilities over possibilities [Krutschke 2015]. This means that a bayesian statistician has an “a priori” opinion regarding the probabilities of an event:
By observing new data x, the statistician will adjust his opinions to get the "a posteriori" probabilities.
The conditional probability of an event d given x is the share of the joint…Continue
Added by Frank Raulf on January 3, 2020 at 4:30am — No Comments
As you might realize by now, writing SQL queries is one of the essential skills any inspiring data analyst needs to master. After all, larger datasets are typically stored in relational databases and Structured Query Language is the language that helps us communicate with such databases. Sure, NoSQL is gaining…Continue
Added by Alex Blyakhman on January 2, 2020 at 8:00pm — No Comments
2019 was a year full of outstanding customer engagements and provocative teaching experiences across numerous universities. My eyes were opened to many new opportunities to integrate economics, design thinking, big data and data science (AI / ML / DL) to further my case for a Nobel Prize in Economics (which I’d prefer not to be awarded posthumously). That includes helping organizations:
Added by Bill Schmarzo on January 2, 2020 at 5:30am — No Comments
The energy sector is under constant development, and more of significant inventions and innovations are yet to come. The energy use has always been involved in other industries like agriculture, manufacturing, transportation, and many others. Thus these industries tend to enlarge…Continue
Finally, a new version of DataMelt (http://jwork.org/dmelt/), a Java-based data-analysis framework based on open-source software, was released. This release features significantly improved graphics to display data and mathematical objects in 3D. The updated canvas (called HPlotXYZ) uses Jzy3d and JOGL 2 to deploy deploy native OpenGL library. A few examples of images with data in 3D…Continue
Added by jwork.ORG on May 25, 2016 at 2:47pm — No Comments