Tag: data driven decision making
Phil Simon shares some lessons from his consulting career.
@philsimon chimes in about how success in one area can lead to success in another.
Jim Harris says a data-driven business can make decisions faster, using better data, with more transparency about results.
Two years ago, I found myself the proud, first-time owner of a garage. My wife and I quickly started to add new items to the garage – a battery-powered lawn mower, two beach cruisers and four Tommy Bahama beach chairs. They were stored with ease. What a fantastic world I'd been missing out on. But it wasn't long before we outstripped our
Applying analytics to IoT data provides opportunities for cities to use information from sensors, citizens and connected infrastructure in unprecedented ways.
What's that productivity related quote by Charles Dickens? "My advice is never do tomorrow what you can do today." For years, machine learning has been written about and discussed widely with a focus on the benefits it will bring in the near future. But guess what? The future for machine learning
It’s great to get in on something on the ground floor. That’s what happened at the inaugural Data4Decisions Conference and Exhibition held in Raleigh, NC, in March. It brought together business people, academics and students to explore how organizations use data management and analytics technology to enhance business processes and
In his pithy style, Seth Godin’s recent blog post Analytics without action said more in 32 words than most posts say in 320 words or most white papers say in 3200 words. (For those counting along, my opening sentence alone used 32 words). Godin’s blog post, in its entirety, stated: “Don’t measure
My previous post explained how confirmation bias can prevent you from behaving like the natural data scientist you like to imagine you are by driving your decision making toward data that confirms your existing beliefs. This post tells the story of another cognitive bias that works against data science. Consider the following scenario: Company-wide
Nowadays we hear a lot about how important it is that we are data-driven in our decision-making. We also hear a lot of criticism aimed at those that are driven more by intuition than data. Like most things in life, however, there’s a big difference between theory and practice. It’s
Data science, as Deepinder Dhingra recently blogged, “is essentially an intersection of math and technology skills.” Individuals with these skills have been labeled data scientists and organizations are competing to hire them. “But what organizations need,” Dhingra explained, “are individuals who, in addition to math and technology, can bring in
Data-driven journalism has driven some of my recent posts. I blogged about turning anecdote into data and how being data-driven means being question-driven. The latter noted the similarity between interviewing people and interviewing data. In this post I want to examine interviewing people about data, especially the data used by people to drive
Oil companies are being forced to explore in geologically complex and remote areas to exploit more unconventional hydrocarbon deposits. New engineering technology has pushed the envelope of previous upstream experience. No guidebook existed on how computing methodologies can contribute to E&P performance at reduced risk. Until now. A new book
When the Apple Macintosh hit the market, analysts were not impressed. But Steve Jobs’ vision ended up transforming our lives. Apple is celebrating its 30th anniversary this year and has become a global household name. Jobs’ ability to direct his organization to develop easy to use products not only met
Valentine’s Day is one of those make-or-break holidays for gift retailers. They are selling "nice to have" items, not necessities. Many use some type of analytics to segment customers for personalized messages. It's not as straightforward as it sounds, especially if the organization hasn't committed to an enterprise-wide approach to
I love working with the Education industry and with our partners and customers. They are always so eager and willing to help that it really makes my job fun and easy. Plus, they are doing some amazing things to help districts, teachers and students. And everyone knows, teachers and schools
We have come very far in our journey (I started this series in March) to the 10 best practices from education customers for information management, reporting and analytics. Lets’ recap our journey of the previous nine blogs: Securing executive sponsorship. Identifying and involving stakeholders early and assessing their unique needs.
We have come very far in our journey to 10 best practices from education customer for information management, reporting and analytics. We are up to Best Practice #9: Empower Users by Providing Training and Self-Help Materials. Most education professionals will need training in order to understand data, reports and analytics.
It is exciting and overwhelming when you first get new software for information management, reporting and analytics. This is especially true once your users first get their hands on the data and new reports. I recall first hand when I was a system engineer and had been with SAS for
In my last post, we discussed the best way to process and deliver reports to stakeholders. So now that that you have launched the portal and users are happily using it, the work doesn’t stop there. Almost immediately, you need to start gathering feedback from users about how they are
As we begin the second half of our series on the 10 best practices for information management, reporting and analytics let’s review what we have learned so far. We now understand the importance of securing executive sponsorship, identifying and involving stakeholders early and assessing their unique needs, identifying and integrating
We are half way through my blog series counting to 10 best practices for information management, reporting and analytics. To recap, we have learned the importance of: Securing executive sponsorship. Identifying and involving stakeholders early and assessing their unique needs. Identifying and integrating data sources. Managing user expectations proactively. This
So far in our journey of the best practices for information management, reporting and analytics, we have learned about the importance of securing executive sponsorship, having a solid understanding of stakeholders needs and integrating all the data needed to make this happen. Now that stakeholders realize that you know their
Data is everywhere,and getting to and managing that information is vital for accurate reporting, analysis and proactive decision making. This brings us to Best Practice # 3: Identify and Integrate Authoritative, Trusted Data Sources. As you might remember, these tips all come from my interviews with SAS education customers. From Best
As I mentioned in my previous blog post, I am sharing best practices that I learned from talking to education customers about successful implement ions of information management, reporting and analytics at their K-12 school district or higher education institutions. In that first post, we learned about the importance of securing executive
In my last blog post I revealed the WOW factor of SAS Visual Analytics. In summary: analyzing billions of rows of data, across vast numbers of columns, via 100+ correlation calculations in SECONDS (wow). What exactly does that mean? SAS Visual Analytics takes full advantage of SAS’ high-performance analytics technology.