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Your data analytics project isn't complete until you package the results in a way that truly helps your client in the business unit make decisions and take action based on your work. That means that analysts not only need to know what the data means but how the recipient of a report can best view and the understand information.
Options for data visualization seem to be growing almost by the day. New technologies and techniques can turn flat, number-intensive reports into bright, colorful 3D interactive graphics. Your approach to delivering results to decision makers will depend on the data and your client's needs. You can help your data tell its story.
Join All Analytics Radio when A2 blogger and Zencos SAS consultant Tricia Aanderud outlines best practices and recent developments in data visualization on Monday, June 22, at 2 pm (EDT). Your presentation options range from an emailed spreadsheet to in-person presentations and dashboards that will serve the business for years to come.
In this interactive session you will learn:
Why you need to consider your visualization and presentation options early in the project lifecycle.
How you can find the right presentation approach for your client.
About some of the new visualization techniques and technologies available to analytics professionals.
The discussion this Friday will focus on the historical bit of data originally used in financing real estate mortgage in the 1800s. This bit of data significantly became the nucleus of understanding the etymology of real estate and its present connotations. Most importantly, the bit of data has metamorphosed into big data sets used within the present real estate transactions (scan through here at http://tinyurl.com/lz45vxn). Information in real estate that were hard to come by or hard deciphered are now readily available to estate agents, buyers, sellers and investors. Explaining and navigating through these capricious sea changes of big data and its global implications on real estate will be the congenial twin of Internet of Things #IoT and Industrial Internet of Things #IIoT. Read more inside here at http://tinyurl.com/o52lwvm
This week discussion will focus on how leaders or team managers decipher variable costs and the limitations of the disruptive components of Big Data. There is limitation on to the insights of the “important data” gleaned from complex, structured and unstructured data that have resulted in about 75 percent of data ultimately becoming useless after 80 days (Leigh, 2013; Tamm-Daniels, 2013). Not only that the overwhelming data collated by DA, DS, IA, OT and IM does become unusable, the limitation are equally intertwined with the analysts, leader’s and manager’s emotional intelligent, intuitiveness, and above all, their prejudice experiences leading to whether or not the data will be skewed subliminally into achieving set organizational objective. Because the raison d’etre of any organization is to maximize profit. There is also this scalable hurdle to jump such as the Information Governance, Sarbanes-Oxley compliance now extended to the use of big data that was initially connected with certifying the accuracy of financial statements under Section 302, “Corporate responsibility and Financial Reports” (Eaton, and et al, 2012; Jarausch and Hardy, 1991). These variables are direct or indirect costs that needed to be implicitly measured in terms of ROI with respect to IoT and IIoT. And the aforementioned will be the topic of examination and lecture this week. Also read more about this discussion inside here at http://tinyurl.com/nky952l
You might be tired of hearing that data scientist is the world's sexiest job, but you can't question the fact that data scientists and other analytics professionals are in demand. That means that you probably won’t find qualified candidates lined up at your door when you post job openings for your analytics team.
Organizations need to know how and where to recruit analytics professionals, whether the search is for highly experienced data scientists or young team members fresh from college.
Research has shown that simply tossing money at candidates isn't a long-term solution. Those candidates will look at your company's growth opportunities, work environment, management talent, range of benefits, and quality and personalities of their potential coworkers. Of course, the paycheck does count too.
Linda Burtch, founder of Burch Works Executive Recruiting, specializes in matching data scientists with new employers, and shares her advice for managers building analytics teams and those who may be testing the job market.
In this session you will learn:
More about the state of the talent pool, and what skills and experiences are available and where hiring demand is strongest
What some analytics positions are commanding for salary and total compensation packages
The types of lifestyle and work-life benefits strong candidates look for
About innovative strategies that successful companies are using to hire and groom great talent
The All Analytics Academy: Building a Successful Analytics Team series continues throughout November.
It's becoming more common to see the terms analytics and data science used interchangeably. However, there is a difference that organizations have to understand, not only when hiring for their data science teams but in shaping their data initiatives.
One way to set data science apart is to consider the use of data that reflects the "Three V's" of Big Data, volume, velocity, and variety. Adam McElhinney, director of data science at predictive analytics company Uptake, joins All Analytics Radio to discuss how those Three V's set apart a data science project. McElhinney, formerly head of business analytics and marketing analytics for Enova Financial, has deep experience in business analytics, credit modeling and credit scoring, consumer finance, business development, performance optimization, strategic planning, and statistical analysis.
Tune into All Analytics Radio at 2 pm (EST) on Monday, November 23, to learn how you can take your analytics initiative to the next level by utililizing those key elements of Big Data: volume, velocity, and variety.
On November 20 my guest will be Brian Rauer, Executive Director of the Mid-Hudson (NY) Better Business Bureau and General Counsel of the Better Business Bureau serving Metropolitan New York. Earlier experience includes the Manhattan based law firm of Plunkett & Jaffe, P.C. Mr. Rauer serves on the Westchester County Consumer Advisory Council and was formerly on the Administrative Law Judge/Hearing Officer roster for the Westchester County Human Rights Commission. He previously served on the Board of Directors of the NY County Lawyers’ Assn. (NYCLA) and on the House of Delegates of the NY State Bar Association. He is a past Chair of the NYCLA Cyberspace Law Committee. He previously served on the Board of Directors of the Association for Conflict Resolution-Greater NY Chapter and the Board of Directors of the NY State Dispute Resolution Assn. Mr. Rauer formerly hosted/presented a regular segment on a nationally syndicated radio show and has presented an extensive array of programs on hot topics of public interest, including privacy/security, ID theft prevention and ethical business practice. He is a Magna Cum Laude graduate of Tulane Law School, receiving the Tulane Law Dean's Medal and selection for the Order of the Coif. Mr. Rauer earned his B.S. degree, Summa Cum Laude, in Business Administration.
What is big data, and why do leaders' gravitates toward big data in making strategic decisions. And why do leaders now depend on big data interpretation for managerial decisions? Simply stated, due to technological situational happenstances, there have been surge of convergences of Information Technology (IT) with the Operational Technology (OT) for strategic decision making. Deft leaders and managers should now collaborate with DS, DA, IA to formulate and set #IoT goals' towards maximization of profit These technological pathways have been changed due to iCloud, Information, Mobile, and Social media, thereby removing all intermediaries from their node. To quickly redact, communication between inanimate objects called the Internet of Things #IoT. And Industrial Internet of Things (IIoT) is where industry communicates with one another like the caterpillar building industry communicating with say with the agricultural department,
On tonight's show Rosie will be sharing visualization techniques to help you improve your ability to heal yourself and others. This show is part 3 in a three part series.
At the bottom of the first hour Rosie will be joined by Leslie Hale, Astrologer for the weekly "Astro-Talk" segment. You can view Leslie's blog at www.lesliehale-astrology.com.
If time allows, Rosie will be accepting calls the last hour of the show. Call in early 1-714-888-7516 for the queue fills quickly.
*The opinions expressed by the guests are for entertainment purposes only and those guests providing comments are theirs alone and do not necessarily reflect the views of the Psychic Viewpoint Show or its host.*
Learn how Big Data is transforming insurance and call center operations, and why your company should be planning Big Data analytics to improve customer loyalty and enhance operating efficiency.
Geoff Colgan from Attadale Partners, brings 25 years of experience leading change management for some of the most accomplished and successful public and private companies in the world. Geoff is a frequent presenter at conferences on topics such as operational performance, change management, and customer experience. Geoff’s work supporting strategy implementation has been referenced in a Harvard Business School case study. Before founding Attadale, Geoff spent almost 20 years serving global clients of Charter Consulting and Gemini Consulting, and in operations at Sun Alliance Life Assurance. As an Australian national, Geoff co-founded and is a past-president of the Australian New Zealand American Chamber of Commerce - Midwest, and remains active in the Australian and Chicago communities. Geoff earned an MBA with high honors from the University of Notre Dame and his bachelor’s degree in economics from the University of Western Australia. Geoff lives in Chicago with his wife and four daughters.
Demand for analytics professionals won't abate soon. Businesses around the world will be looking to hire young analytics professionals to support their big data initiatives. Those businesses will need analytics/data science professionals who are strong in data management, modeling, visualization, and other technical skills, but they also require business experience.
Yes, the two worlds of technology and business can meet. Dr. Goutam Chakraborty, a professor of marketing at Oklahoma State University, is heading up a new masters in analytics program, based on what he has learned leading the school's previous certificate program. The new program will expose students to statistics, of course, but will also draw on staff expertise in information science, industrial engineering, and marketing.
In this All Analytics Radio program, Dr. Chakraborty will share his experience and his advice on crafting an analytics program for the future, one that will prepare young data scientists to step into the business world ready to contribute to an analytics initiative, and he will help employers understand what they can expect from the classes of 2018 and beyond.
In this show you will learn:
About the strategies that colleges are using to shape an analytics workforce for the future
How colleges and employers can work together to define curricula and internships
About what type of impact today's undergraduate and graduate data science programs can have in closing the analytics skills gap.
Join us at 2 pm (ET) on Tuesday, October 20, on All Analytics Radio.
It is said that what is measured, is what is capable of change. But everything can be measured and everything can be changed overnight. However, 65% of change efforts fail and yes, some of that is attributed to the change management process, but come on let's not put all of the accountability on the change management folks. What about the data analysis and findings that gave life to the change? Yes, data does lie. And that's because numbers can tell you what you want them to tell you. There are a lot of qualitative data that are overlooked everyday in organizations because they are easier to put into an excel sheet and present for buy-in decisions, not because they are the whole truth. During this episoce, we will discuss one area that Data is highly used, yet not necessarily in the most effective way.
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