Want to apply Data Science to Business Process Management? Have a look at process mining, explained in this poster!
Added by Linda Terlouw on January 27, 2015 at 2:00am — No Comments
The purpose of Financial Modeling is to build a Financial Model which can enable a person to take better financial decision.The decision could be affected by future cash flow projections , debt structure for the company etc. All these factors may affect the viability for a project or investment in a company.The Applications of Financial Modeling mainly includes the followings :
Added by rajesh dhnashire on January 26, 2015 at 11:00pm — No Comments
This is an update to our December 2013 article: 6000 companies hiring data scientists. Microsoft and IBM still dominate, but we've seen some shift over the last 12 months:
I always make the point that data is everywhere – and that a lot of it is free. Companies don’t necessarily have to build their own massive data repositories before starting with big data analytics. The moves by companies and governments to put large amounts of information into the public domain have made large volumes of data accessible to everyone.
Any company, from big blue chip corporations to the tiniest start-up can now leverage more data than ever before. Many of my clients ask…Continue
There is often confusion between the definitions of "data veracity" and "data quality".
Data veracity is sometimes thought as uncertain or imprecise data, yet may be more precisely defined as false or inaccurate data. The data may be intentionally, negligently or mistakenly falsified. Data veracity may be distinguished from data quality,…Continue
Often, Data Science for IoT differs from conventional data science due to the presence of hardware.
Hardware could be involved in integration with the Cloud or Processing at the Edge (which Cisco and others have called Fog Computing).
Alternately, we see entirely…Continue
Added by ajit jaokar on January 25, 2015 at 12:30pm — No Comments
"Today, India ranks second worldwide in farm output. The economic contribution of agriculture to India's GDP is steadily declining with the country's broad-based economic growth. Still, agriculture is demographically the broadest economic sector and plays a significant role in the overall socio-economic fabric of India." - From Wikipedia…Continue
Added by VINU KIRAN .S on January 24, 2015 at 1:00am — No Comments
The years leading up to 2015 affirmed and reaffirmed that we indeed have lots of data. And with lots of data all around us, organizations should really be thinking about how to leverage data to get ahead not only of competition but to get ahead of everyday transactions and to be able to predict and control what's coming down the pike. Almost every transaction in society now is ‘datafied.' The automation and datafication of transactions and actions are giving us the opportunity to understand…Continue
Added by B.J. Gonzalvo, PhD on January 23, 2015 at 3:44pm — No Comments
The other day, I found myself feeling exceptionally tired, not getting much work done even though it was 11:30 in the morning.…Continue
Added by John Irvine on January 22, 2015 at 6:30pm — No Comments
If you work with data regularly, chances are you trust it. You know how it's collected and stored. You know the caveats and the roadblocks you face…Continue
Here is my selection of time-insensitive best articles, that were viewed more than a thousand times each, in 2014.
Single-starred articles are written by external/guest bloggers. Our upcoming book on data science 2.0 will be based on some of these (edited and…Continue
Added by Vincent Granville on January 21, 2015 at 1:53pm — No Comments
The full version is always published Monday. Starred articles or sections are new additions or updated content, posted between Thursday and Sunday.
Added by Vincent Granville on January 21, 2015 at 11:30am — No Comments
Added by Linda Terlouw on January 21, 2015 at 11:00am — No Comments
Human resources analytics can provide businesses the keys to improving processes, reducing workforce costs and making the right policy changes to improve efficiency. Leaders in the space and speakers from the upcoming…Continue
Added by Alesia on January 20, 2015 at 12:00pm — No Comments
For any data science project, if you start with the wrong question, you are bound to end up with the wrong answer, and fail. Who should identify the right question? I believe data scientists should be involved in the process, otherwise, they will be held responsible for the failure.
CDC headquarters in Druid Hills,…Continue
Added by Vincent Granville on January 19, 2015 at 6:30pm — No Comments
I thought I would share it on here in case anyone is interested.
The project can be found here: http://rpubs.com/Mandypar/54270
And the course I am doing is described here: https://www.coursera.org/course/repdata
It would be fun to go into more detail for this, but I have more than filled the project brief and have run out…Continue
Added by Mandy Parmenter on January 19, 2015 at 9:34am — No Comments
Guest blog post by Bernard Marr.
In my last post, I explained the difference between what I consider the two core types of data scientist – strategic and operational.
Broadly speaking, they require many of the same skillsets – but the distribution of your expertise and experience within these skillsets will vary, depending on whether…Continue
In my previous blog on the Hopscotch and Robots simulation environment, I discussed the use of structural data extracted from hypothetical and real-life organizational events. In the current blog, I will be briefly covering conceptual issues more focused on the nature of the structural data itself including its theoretical significance.
Structural data holds information about the relationship between events.…Continue
Added by Don Philip Faithful on January 18, 2015 at 8:10am — No Comments
I am a newbie to Bigdata and would like to highlight some significant advantages if incorporated in a company's supply-chain management strategies, expecting the reader's views and suggestions.
Because, in recent past I have developed a online supply-chain management systems in which sellers and customers are matched using an algorithm. It acted as a decision support system and I needed to dig deeper on the available data to get more insights over the data pattern (even for…Continue