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Business analytics

What’s the difference between Business Analytics and Business Intelligence? The correct answer is: everybody has an opinion, but nobody knows, and you shouldn’t care.

Having worked in the industry over twenty years, I can confidently say that everybody has a different notion of what ANY particular term associated with analytics means.

For example, when SAP says business analytics instead of business intelligence , it s intended to indicate that business analytics is an umbrella term including data warehousing, business intelligence, enterprise information management, enterprise performance management, analytic applications, and governance, risk, and compliance.

But other vendors (such as SAS) use business analytics to indicate some level of vertical/horizontal domain knowledge tied with statistical or predictive analytics.

At the end of the day, there are two things worth differentiating:

  1. The first is the business aspect of BI the need to get the most value out of information. This need hasn t really changed in over fifty years (although the increasing complexity of the world economy means it s ever harder to deliver). And the majority of real issues that stop us from getting value out of information (information culture, politics, lack of analytic competence, etc.) haven’t changed in decades either.
  2. The second is the IT aspect of BI what technology is used to help provide the business need. This obviously does change over time sometimes radically.

The problems in nomenclature typically arise because “business intelligence” is commonly used to refer both of these, according to the context, thus confusing the heck out of everyone.

In particular, as the IT infrastructure inevitably changes over time, analysts and vendors (especially new entrants) become uncomfortable with what increasingly strikes them as a dated term, and want to change it for a newer term that they think will differentiate their coverage/products (when I joined the industry, it was called “decision support systems” – which I still think is a better term in many ways).

When people introduce a new term, they inevitably (and deliberately, cynically?) dismiss the old one as just technology driven and backward looking , while the new term is business oriented and actionable .

This is complete rubbish, and I encourage you to boo loudly whenever you hear a pundit say it.

The very first use of what we now mostly call business intelligence was in 1951, as far as I can tell, with the advent of the first commercial computer ever, dubbed LEO for Lyons Electronic Office, powered by over 6,000 vacuum tubes. And it was already about “meeting business needs through actionable information”, in this case deciding the number of cakes and sandwiches to make for the next day, based on the previous demand in J. Lyons Co. tea shops in the UK.

And It most emphatically was not “only IT” or “only looking in the rear-view mirror” as some people pompously try to dismiss “old-style BI”.

At the end of the day, nobody important cares what this stuff is called. If you’re in charge of a project, what matters is working out the best way to leverage the information opportunity in your organization, and putting in place appropriate technology to meet that business need and you can call that process whatever you like: it won t make any difference

If you have strong opinions on the topic, you may want to join in on this thread on the the brand new, business-oriented forum on the SAP Community Network. In the meantime, here’s why I changed the name of this blog from “BI questions” to “Business Analytics” a few months ago:

Google Trends on “business intelligence” – slow decline (note this is relative to overall search volume, not absolute)

Business analytics

Business analytics



Business Analytics

Harness real-time insights for better business results

Data that’s out of context and out of date can derail even the best efforts to proactively manage labor-related challenges, such as adjusting staff skill levels/competencies and controlling staffing costs.

Designed specifically for the 24/7 healthcare environment, our integrated Centricity TM Business Analytics delivers deep insight into all areas that impact your ability to deliver high quality care while controlling labor costs.

Did you know? Healthcare executives say their top workforce management issues are controlling overtime and improving the skill level/competency mix.

Optimize resource distribution by accessing a broad view of labor across every department, allowing you to quickly spot trends and make agile adjustments.

Empower managers with real-time labor analytics to make on-the-fly staffing adjustments. Our solution doesn’t just point out problems; it shows how to fix them.

Meet quality care goals by ensuring properly skilled staff are in the right place at the right time.

Control overtime with business analytics that profile your labor landscape in dollars as well as hours.

Prevent avoidable overtime with labor analytics that compare actual time worked with future schedules, alerting them to incidental and preventable overtime.

Make targeted moves to increase productivity by accessing time and attendance data to evaluate staff efficiencies in relation to work performed. Understanding where to improve efficiencies is key to keeping performance elevated and quality high

Now more than ever, creating a link between the clinical and financial sides of the healthcare business is essential to delivering cost-effective, quality patient care enterprise-wide. To learn more about how we can help, we invite you to read:



Executive Degree Programs

Business analytics

Graduate Certificate in Business Analytics

Business Analytics

Business analytics specialists are in demand across the global market.

Data. Every company produces it. But not every company is leveraging it. Why? Because many times, companies don t have the right person to lead the charge. Data alone can t provide clear-cut recommendations.

Program dates and deadlines

Enhance your analytical skills in less than 12 months.

The Kelley School of Business is one of the top 20 business schools in the country. The course content offers the scope and depth of knowledge and expertise found in any Kelley School of Business classroom.

Business analytics courses combine the skills, technologies, applications and processes used by organizations to gain data-driven insights. These insights can be used to aid decision-making across functions including finance, marketing and operations.

Certificate cost and requirements

Professional certificates from the Kelley School of Business are designed to be flexible and cost-effective.

Your Business Analytics Certificate will:

  • Total 12 credit hours
  • Cost $1,145 per credit hour
  • Be completed over the course of 12 months
  • Consist of four courses, 3 credits per course, taught sequentially
  • Be completed fully online
  • Not require GMAT/GRE scores

A bachelor s degree is required for this certificate.

Transfer your certificate credits to an online degree program

Earning a professional certificate is a low-risk way for you to explore a field of business, and decide if you want to continue developing your expertise in that area.

Executive Degree Programs makes it easy for you to earn an MBA or MS online. Simply apply your certificate credits to your MS degree requirements.

You can apply your certificate credit to the following degrees:

Course curriculum

The three components of the business analytics curriculum are:

Business analytics

Business analytics

Business analytics

Of your four required courses, your first will provide an overview of business analytics. The remaining three courses will each focus on one of the components listed above.

C531: Introduction to Business Analytics

  • Define and explain the business analytics process (problem definition; data preparation; technical analysis and modeling; evaluation of results; implementation and deployment).
  • Understand and describe the functionality and role of analytic techniques in data mining and predictive analytics.
  • Perform basic and advanced analytics tasks with JMP and Excel.
  • Construct, validate, and interpret data mining and predictive analytics models using large multivariate data sets.
  • Apply data mining and predictive analytic techniques to problems in areas such as fund raising, retailing, direct marketing, market segmentation, bankruptcy prediction, credit scoring, and fraud detection.
  • Perform data exploration to evaluate variables for data mining and to suggest and implement approaches to handle data problems such as missing values, outliers, and skewed distributions.
  • Compute and interpret key predictive accuracy measures and methods including lift charts, gain charts, and ROC curves.

C533: Data Warehousing Visualization

  • Understand and utilize unsupervised models including principal components analysis, cluster analysis, and market basket analysis. Understand business intelligence-related concepts
    • The notion of corporate information factory.
    • Dashboards and scorecards that support the businesses.
    • Different types of problems related to data quality including a methodology for maintaining data quality.
    • An overview of variety of software tools that are employed in the development of a data warehouse: ETL (extraction, transformation and loading) and analytic tools.
  • Recognize some of the key issues for managerial considerations
    • The tools of metrics in decision making
    • Types of business risks along with how to alleviate the risks associated with implementing informational systems
    • Issues related to data governance
  • Be cognizant of a variety of tools and techniques

C534: Simulation and Optimization for Business Analytics

  • Develop analytical models using simulation and optimization to analyze and recommend sound solutions to complex business problems
  • Develop models to provide solutions to operational problems in various business functional areas including finance, economics, operations, and marketing
  • Solve complex problems using various tools on spreadsheets; including Excel solver for linear and integer programming problems, @RISK for probabilistic simulations, and risk analysis
  • Undertake input and output statistical analysis for simulation models
  • Solve complex optimization problems using the ILOG-CPLEX package

C535: Developing Value through Business Analytics Applications

  • Understand how various analytical techniques and tools are used to analyze complex business problems and derive business value for applications
  • Apply analytical techniques to various retail and marketing problems; including determining customer value and using the concept to aid in business decision making by allocating marketing expenditures between customer acquisition and customer retentions (Marketing Analytics)
  • Apply EXCEL financial functions (XIRR, XNPV, FV, PV, PMT, CUMPRINC, and CUMIPMT) and develop models to solve financial problems on spreadsheets (Financial Analytics)
  • Develop inventory models under uncertainty including service level and reorder point models for supply chains (Supply Chain Analytics)
  • Deploy analytics, such as aggregate planning models in production planning and scheduling (Operations Analytics)
  • Use Data Envelopment Analysis (DEA) in solving various healthcare problems (Healthcare Analytics)

Apply now for the Business Analytics Graduate Certificate.

Part 1: Kelley Application: fill out this online application first.

Part 2: Indiana University Application.

After you fill out the Kelley application, you ll receive an email with instructions on how to apply through the IU application. During this Part 2 application, you will upload the following materials to complete your application.

  • Resume Provide a copy of your resume, summarizing your professional experiences and accomplishments.
  • Personal Statement Tell us what you want to achieve in this program in 500 words or less.
  • Letter of Recommendation Ask someone who knows your professional career to write a letter of recommendation for you. Provide the contact information of your recommender within the application. An email prompt will be sent to their email address, and they will be able to fill out a form and upload additional material. If you need alternative arrangements, please contact [email protected]
  • Post-Secondary Transcripts Provide copies of your transcripts from all of the post-secondary institutions you ve attended. These copies can be sent to the program manager, or uploaded into the Part 2 Application.

If you have any questions about the application process, or you want to send your transcripts by mail, contact:



Business Analytics

Business analytics

Business Analytics solutions allow employees to visualize trends and even predict potential outcomes.

Business Analytics is a broad term used to describe computer software solutions that help users tap into enterprise data to make better, more informed business decisions. Through the use of business analytics solutions, organizations can instantly identify the factors that impact their performance, create more accurate forward-looking strategies, enhance efficiency, increase profitability, and improve customer satisfaction and loyalty. Predictive analytics, social media analytics, data visualization, data mining, enterprise search, and location analytics and mapping solutions are among the many tools available in the business analytics category.

With business analytics in place, users can retrieve, combine, and explore data from a wide array of internal and external sources to uncover and decipher patterns, trends, relationships, and anomalies. Business analytics can also enable users to conduct accurate forecasts, anticipating future events or results based on historical information, or to evaluate “what if” scenarios to determine how changes to certain factors will impact outcomes. “What if” analysis can be particularly valuable in certain marketing, merchandising, and pricing scenarios. The ability to present data via sophisticated, compelling images, or on intuitive maps is another key capability of many business analytics solutions.

Interested in finding out more about Business Analytics? Check out this free white paper:

Business analytics can provide a competitive advantage to companies large and small. But, they can be particularly important in situations where “big data” exists. The massive volumes of information maintained by many business today – which can total terabytes, petabytes, exabytes, and even zettabytes of data in some industries – has made it harder than ever to uncover and truly understand game-changing patterns and trends through traditional reporting methods. Advanced analytics can provide an effective means of collecting, cleansing and correlating, and analyzing all that data.

Information Builders offers a wide array of innovative, market-leading analytics solutions. We can help organizations exploit enterprise information to facilitate faster, smarter planning and better decision making.

  • WebFOCUS RStat, a powerful predictive analytics solution that bridges the gap between backward- and forward-facing views of business operations to enable accurate, validated forecasting of future events or conditions
  • WebFOCUS Visual Discovery, a cutting-edge data visualization solution that depicts enterprise information in stunning and appealing graphical representations, such as 3D bar and pie charts, histograms, scatter plots, and more
  • Location intelligence, seamless integration with leading mapping solutions from ESRI (ArcIMS and ArcGIS), Google (Google Maps), and Adobe® Flex®, allowing for visualization of the spatial component of any business data
  • WebFOCUS Magnify, a robust enterprise search facility that makes it easy to index, locate, and retrieve both structured and unstructured data, regardless of its source or location


Business Analytics

Harness real-time insights for better business results

Data that’s out of context and out of date can derail even the best efforts to proactively manage labor-related challenges, such as adjusting staff skill levels/competencies and controlling staffing costs.

Designed specifically for the 24/7 healthcare environment, our integrated Centricity TM Business Analytics delivers deep insight into all areas that impact your ability to deliver high quality care while controlling labor costs.

Did you know? Healthcare executives say their top workforce management issues are controlling overtime and improving the skill level/competency mix.

Optimize resource distribution by accessing a broad view of labor across every department, allowing you to quickly spot trends and make agile adjustments.

Empower managers with real-time labor analytics to make on-the-fly staffing adjustments. Our solution doesn’t just point out problems; it shows how to fix them.

Meet quality care goals by ensuring properly skilled staff are in the right place at the right time.

Control overtime with business analytics that profile your labor landscape in dollars as well as hours.

Prevent avoidable overtime with labor analytics that compare actual time worked with future schedules, alerting them to incidental and preventable overtime.

Make targeted moves to increase productivity by accessing time and attendance data to evaluate staff efficiencies in relation to work performed. Understanding where to improve efficiencies is key to keeping performance elevated and quality high

Now more than ever, creating a link between the clinical and financial sides of the healthcare business is essential to delivering cost-effective, quality patient care enterprise-wide. To learn more about how we can help, we invite you to read:



#business data

#

Arkansas Tech University

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Business Data Analytics

The Business Data Analytics major prepares students for a career in business data analysis. These professionals analyze data to support business decisions and strategy and to creatively solve business problems. Specific data analyst job descriptions depend on the responsibilities of the particular industry in which the data analyst is working. For example, a data analyst working in the health care sector will be expected to perform data analysis with respect to patient outcomes, customer and insurance payment patterns, drug interactions, infection rates, geographic health care service densities, and other types of health care data. Similarly, a data analyst working in customer relationship management will be expected to perform data analysis with respect to customer buying patterns, identifying the best and worst customers, identifying different customer types, detecting fraud, and identifying opportunities for cross-selling and up-selling. A data analyst responds to client or management requests for information and may have to develop methodologies and files for effective data management.

Resources

Contact

A data analyst is able to retrieve, manipulate, and analyze data from multiple sources. He or she works with data using a variety of tools, platforms, and techniques and interprets the results in a clear, understandable way. These professionals create and report actionable information in a professional manner. Through a strong understanding of software, database/data warehouse, and research tools, the Business Data Analyst combines an understanding of business functional requirements, information resources, and systems applications of a firm to create and manage meaningful business intelligence to achieve business strategic success.

Specific objectives of the program are to provide students who select the Business Data Analytics major with the following:
  1. Ability to use technology to manage and analyze data to create information to support business decisions and solve business problems.
  2. Overall communication skills in the context of determining information requirements and conveying business data analysis results to clients.
  3. Ability to think critically and reason effectively about the quality of data and data analysis procedures in the context of creating information to solve business problems.
  4. Ethical awareness and ethical decision-making framework in a business data analysis context.
  5. Ability to use foundation business knowledge in data analysis in a diverse, global environment.
The Business Data Analytics program course examination procedures include:
  • Case analysis
  • Semester research papers/projects
  • Practical computer skills proficiency projects
  • Multiple choice/short answer/essay exams

2015 Arkansas Tech University | All Rights Reserved
215 West O Street, Russellville, Arkansas 72801 USA
For general information call (844) 804-2628
All trademarks herein belong to their respective owners



#harvard business journal

#

KDnuggets

30 Can t miss Harvard Business Review articles on Data Science, Big Data and Analytics

Here are 30 Harvard Business Review (HBR) articles on big data, data science and analytics that provide insights about the latest technology and happenings in the world of data.

There are dozens of HBR articles that are worth recommending, but here are our picks on big data, data science and analytics collected using most popular and next recommended article filters based on search term.


Full Disclosure. You can view 5 articles per month without the need to sign up and upto 15 articles can be accessed after sign up. KDnuggets derives no form of benefit if you subscribe to HBR.

On Data Science

  1. Data Scientist: the sexiest job of the 21st centuryby Thomas H. Davenport and D.J. Patil (Oct 2012)
    How the idea of LinkedIn’s People You May Know feature really clicked! The key player involved was a “Data Scientist”, a title coined by the two authors.
  2. The Sexiest Job of the 21st Century is Tedious, and that Needs to Changeby Sean Kandel (Apr 2014)
    Which phase does a data scientist spend more time on? Data Discovery, data structuring and creating context. Should they shift their focus?
  3. What Every Manager Should Know About Machine Learningby Mike Yeomans (July 2015)
    With the right mix of technical skill human judgment, machine learning could be a new tool for decision makers. Learn what mistakes to avoid.
  4. Data Scientists Don’t Scaleby Stuart Frankel (May 2015)
    We are at a new phase of big data. Is Data capture and storage now less relevant than making it more useful impactful?
  5. Get the Right Data Scientists Asking the “Wrong” Questionsby Josh Sullivan (Mar 2014)
    What makes an exceptional data scientist? Data by itself is meaningless. The skill curiosity is what makes the difference.
  6. A Data Scientist’s Real Job: Storytellingby Jeff Bladt and Bob Filbin (Mar 2013)
    How to derive insights intuitions from data? We “humanize” the data by turning raw numbers into a story about our performance.
  7. What Separates a Good Data Scientist from a Great Oneby Thomas C. Redman (Jan 2013)
    Better than the Best! Great data scientists bring four mutually reinforcing traits to bear that even the good ones can’t.
  8. Still the Sexiest Profession Aliveby DJ Patil (Nov 2013)
    Data scientist jobs are very much in demand as companies grapple with the challenge of making valuable discoveries from Big Data. Is a huge crowd just joining the bandwagon?
  9. 10 Kinds of Stories to Tell with Databy Tom Davenport (Nov 2013)
    Narrative is—along with visual analytics—an important way to communicate analytical results to non-analytical people. Explore the 10 types.
  10. How to Start Thinking Like a Data Scientistby Thomas C. Redman (Nov 2013)
    You don’t have to be a data scientist or a Bayesian statistician to tease useful insights from data. The author demonstrates how to think with a small exercise.
  11. Stop Searching for That Elusive Data Scientistby Michael Schrage(Sep 2014)
    Stop hunting for that data science unicorn and/or silver bullet. What to do instead?
  12. How to Explore Cause and Effect Like a Data Scientistby Thomas C. Redman (Feb 2014)
    While we can use data to understand correlation, the more fundamental understanding of cause and effect requires more.

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#business information

#

Graduate Studies Office

Business Information and Analytics Systems MSc

College: Business and Law

Duration: 12 months Full-time

Teaching Mode: Full-time

Costs: 2016/2017 Irish/EU fee €9,000. There will be field trips which are not covered by the course fee.

2016 Entry Requirements: See detailed entry requirements

Closing Date: EU Applicants: Open For Late Applications 2016.

Next Intake: September 2016

Business Analytics enables organisations exploit the data and IS systems at its disposal to maximise organisational performance. Students will develop the skills necessary to gain business insights to improve decision-making.

The MSc in Business Information and Analytics Systems provides students with a portfolio of business and analytical methods for solving problems and supporting decision making. The MSc BIAS provides students with a specialism in Business Analytics as well as an extensive knowledge of business and IS concepts. At the core of this programme is a selection of topics covering cloud technologies, Business Intelligence and Business Analytics, IT performance management. data management and IT project management. A research project will allow student groups to explore and develop an IT solution to a specific business problem in an area specific to the Business Information and Analytics area.

Business Analyst and Project Manager are listed as two of the top ten jobs in the IS / IT sector[1]. The MSc Business Information and Analytics (MSc BIAS) is designed to provide students with the skillset to be successful in these roles. Organisations today need people who know how to manage and store data that helps them make better business decisions, compared to years ago when businesses didn’t have data management at their fingertips to review and analyse to help them drive business forward.

The MSc in Business Information and Analytic Systems degree offers a specialisation in Business Analytics with modules such as:

  • Design thinking for the Business Analyst
  • Business Data Strategy
  • Data Visualisation
  • Business Analytics and Business Intelligence
  • Cognitive Decision Making and DSS

These modules will allow students to acquire the skills to mine and analyse data in ways that will enable more informed decision making and result in better outcomes for the organisation. How organisations capture, create and use data is changing the way we work and live. Businesses have more data readily available than ever before and are aware of the need to understand the underlying messages that are held within their data. However, discovering and identifying the underlying message requires a higher level of thinking and analysis.

Additionally the course offers a curriculum of core IS modules including:

  • Cloud Technology
  • Data Acquisition and Management
  • Project Management
  • IT and Organisational Performance
  • Enterprise Business Processes

These core modules provide students with the technical skills and techniques needed by organisations to explore organisational issues and support decision-making within a business context. These skills are essential in any organisation where IT is integral to the success of the business. A group research project facilitates students in the practical application of the Information Systems and Business analytical skills that are acquired during the programme.

Eligibility for the MSc BIAS requires candidates to have a 2.2 primary degree at NFQ Level 8 Honours Degree or equivalent, with appropriate information systems or computing technology skills content. You may also be admitted to the course on the basis of extensive practical or professional experience, as deemed appropriate by the Professor of Business Information Systems and the School of Business. Typical students are from technical disciplines such as, Management Information Systems (MIS) or Business Information Systems (BIS), engineering, computer science and mathematics. It is also suitable for business and humanities graduates who have studied computer science and Business Information Systems (BIS) subjects with some computer programming content.

Application for this programme is on-line at www.pac.ie/ucc. Places on this programme are offered in rounds. The closing dates for each round can be found here. For full details of the application procedure click How to apply.

Please note that you will be asked to fill in a supplementary form as part of the application process for this programme. A copy of this form is available here CKL51 MSc (Business Information Analytical Systems Suppl Form (17kB)

All required documentation must be sent in hard copy to The Postgraduate Applications Centre, 1, Courthouse Square, Galway.

The School of Law uses a system of offer rounds to facilitate decision-making and early notification to applicants. Candidates are encouraged to apply as early as possible. Candidates who do not have their final degree marks available may be made a conditional (provisional) offer.

New applications will continue to be reviewed at each round if there are still programme places available.

16 lecture hours per week, with 2 hours of lab work per week. Between 3 and 5 field trips will be organised throughout the year. Group project work continues to early July at the latest, concluding the formal course content. However, students may be required to complete an individual essay in their own time up until the end of July/early August.

A hybrid approach to assessment is used in this programme. Assessments methods include formal written exams, essays, group and individual project work and some lab practicals. Some modules are 100% continuous assessment and most modules have a minimum of 40% continuous assessment. During the programme, students will work individually and in groups. A strong emphasis is placed on oral presentation of work.

The course is taught by academic staff from the Cork University Business School. The academics who teach on the course are experts in their field. These lecturers all have PhDs and/or significant industry experience. Several of the Faculty have worked previously at leading IT organisations, major banks and research agencies. Our academic staff are also engaged in research with involvement in or leadership of research centers in UCC, and publish regularly in international peer-reviewed IT / IS and business journals.

Name: Dr Mary Daly



#harvard business journal

#

KDnuggets

30 Can t miss Harvard Business Review articles on Data Science, Big Data and Analytics

Here are 30 Harvard Business Review (HBR) articles on big data, data science and analytics that provide insights about the latest technology and happenings in the world of data.

There are dozens of HBR articles that are worth recommending, but here are our picks on big data, data science and analytics collected using most popular and next recommended article filters based on search term.


Full Disclosure. You can view 5 articles per month without the need to sign up and upto 15 articles can be accessed after sign up. KDnuggets derives no form of benefit if you subscribe to HBR.

On Data Science

  1. Data Scientist: the sexiest job of the 21st centuryby Thomas H. Davenport and D.J. Patil (Oct 2012)
    How the idea of LinkedIn’s People You May Know feature really clicked! The key player involved was a “Data Scientist”, a title coined by the two authors.
  2. The Sexiest Job of the 21st Century is Tedious, and that Needs to Changeby Sean Kandel (Apr 2014)
    Which phase does a data scientist spend more time on? Data Discovery, data structuring and creating context. Should they shift their focus?
  3. What Every Manager Should Know About Machine Learningby Mike Yeomans (July 2015)
    With the right mix of technical skill human judgment, machine learning could be a new tool for decision makers. Learn what mistakes to avoid.
  4. Data Scientists Don’t Scaleby Stuart Frankel (May 2015)
    We are at a new phase of big data. Is Data capture and storage now less relevant than making it more useful impactful?
  5. Get the Right Data Scientists Asking the “Wrong” Questionsby Josh Sullivan (Mar 2014)
    What makes an exceptional data scientist? Data by itself is meaningless. The skill curiosity is what makes the difference.
  6. A Data Scientist’s Real Job: Storytellingby Jeff Bladt and Bob Filbin (Mar 2013)
    How to derive insights intuitions from data? We “humanize” the data by turning raw numbers into a story about our performance.
  7. What Separates a Good Data Scientist from a Great Oneby Thomas C. Redman (Jan 2013)
    Better than the Best! Great data scientists bring four mutually reinforcing traits to bear that even the good ones can’t.
  8. Still the Sexiest Profession Aliveby DJ Patil (Nov 2013)
    Data scientist jobs are very much in demand as companies grapple with the challenge of making valuable discoveries from Big Data. Is a huge crowd just joining the bandwagon?
  9. 10 Kinds of Stories to Tell with Databy Tom Davenport (Nov 2013)
    Narrative is—along with visual analytics—an important way to communicate analytical results to non-analytical people. Explore the 10 types.
  10. How to Start Thinking Like a Data Scientistby Thomas C. Redman (Nov 2013)
    You don’t have to be a data scientist or a Bayesian statistician to tease useful insights from data. The author demonstrates how to think with a small exercise.
  11. Stop Searching for That Elusive Data Scientistby Michael Schrage(Sep 2014)
    Stop hunting for that data science unicorn and/or silver bullet. What to do instead?
  12. How to Explore Cause and Effect Like a Data Scientistby Thomas C. Redman (Feb 2014)
    While we can use data to understand correlation, the more fundamental understanding of cause and effect requires more.

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  2. 7 Steps to Mastering Machine Learning With Python
  3. 21 Must-Know Data Science Interview Questions and Answers
  4. Bayesian Machine Learning, Explained
  5. How to Become a Data Scientist – Part 1
  6. Why Big Data is in Trouble: They Forgot About Applied Statistics
  7. Data Science for Beginners: Fantastic Introductory Video Series from Microsoft
  1. The 10 Algorithms Machine Learning Engineers Need to Know
  2. Data Science for Beginners: Fantastic Introductory Video Series from Microsoft
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  7. Reinforcement Learning and the Internet of Things


#business intelligence

#

Business Intelligence Analytics

Explore all your data. Discover new patterns. Create rich visuals and share insights. With easy-to-use analytics and business intelligence tools from SAS, you can:

  • Get the picture. Fast. Get blazingly fast insights by visually exploring all relevant data. Spot unknown patterns. Identify key relationships. And unearth hidden opportunities.
  • See it. Understand it. Compelling visuals help you quickly grasp what the data has to tell you. Interactive visualizations backed by analytics are explained in terms everyone can understand.
  • Stop guessing. Work smartly. Streamline data preparation. The software automatically highlights relevant findings and significant discoveries for you – no coding required.
  • It’s easy. No matter your skill level, you can ask tough questions. Easily explore, create and share. Follow your instincts. No need to engage IT.
  • Fast insights from any data. Whether it’s in Hadoop, your data warehouse or Microsoft Office spreadsheets, you can discover data from any source in a well-governed way – without preconceptions.
  • Pictures with impact. Our visualizations and dashboards are powered by SAS Analytics. Automatically. No coding required.

Ready to take the next step toward getting the most value from your data? We offer several different technology, deployment and financing options, depending on your needs.

Put the world’s most powerful analytics in everyone’s hands, and your organization will reap the rewards. With SAS, you can:

  • Find the metrics that matter most. Identify outliers. Spot correlations. Pinpoint exceptions. Forecast trends. Predict outcomes. Quickly. Visually. And gain a competitive advantage without building models.
  • Expand your analytics culture. With approachable analytics that anyone can use and understand, you’ll foster acceptance and encourage adoption.
  • Go way beyond descriptive analytics. What do you get when you combine interactive reporting with self-service analytics? A collaborative environment where everyone can answer why? and what’s next?
  • Business intelligence with brains and brawn. Identify and share insights and performance metrics based on foresight, not hindsight. We’ve combined BI tools with analytics – backed by nearly 40 years of expertise – to give you THE POWER TO KNOW ® .
  • A smarter way to run your business. Behind-the-scenes algorithms – to detect what’s significant and relevant – along with brilliant visualizations present data in the best possible way for quick assessment. So you won’t miss important, contextual findings.
  • Easy enough for anyone. You don’t have to be a rocket scientist – or a data scientist – to use analytics. Our drag-and-drop approach lets you change queries quickly, so there are no barriers to experimentation and discovery.

Ready to take the next step toward getting the most value from your data? We offer several different technology, deployment and financing options, depending on your needs.

Is it possible to satisfy business users (who want to create their own BI content) and IT (who wants to selectively manage and govern it)? Yes. With SAS, you can:

  • Do it yourself, and set IT free. The self-service, ad hoc reporting environment lets you create distribution-quality reports and analytics dashboards without burdening IT. No more waiting; you’re in control.
  • Keep governance alive. IT and BICC staff can select business-user-generated BI content for production to promote proper governance.
  • Enjoy the freedom of self-service data preparation. Basic capabilities for data access, mashup, filtering and data transformation are built into our BI tools – just right for the business analyst.
  • Closing the gap. A managed, self-service BI approach will close the gap between business and IT – not drive them further apart. You’ll reduce risks and gain the flexibility to act quickly.
  • Equal opportunity, whether executive, analyst or citizen data scientist. Share reports, charts and analytic content via the web, PDF files or mobile devices. Improve business knowledge and productivity. And make informed decisions.
  • Consumer-grade interactivity. Enable business-user-led report authoring and reshaping using only items of interest. Easily embed reports and charts with other content sources, applications or portals while retaining full interactivity.

Ready to take the next step toward getting the most value from your data? We offer several different technology, deployment and financing options, depending on your needs.

The world is built on teamwork. So why not put business intelligence and analytics where they can add more value? With SAS, you can:

  • Put analytics and BI tools where people work most. Only SAS drives faster adoption by surfacing results and key insights in Microsoft Office applications, including Outlook and Excel.
  • Exchange ideas and insights. Business users can easily create storyboards or narratives and have meaningful conversations about results.
  • Foster alignment for better business decisions. Spread the word with visual insights, and expand the reach of information. Interactive commenting and annotations promote consensus building.
  • Easy to use and collaborate. Promote idea sharing while saving valuable time. You can annotate reports or charts, then send to others, who can add their thoughts as well. Or capture comments via video and audio.
  • Everyday email becomes everyday BI. Deliver consistent analytic insights and BI to your users via email, without filling up inboxes. And there’s no need to open other applications to view reports.
  • Consistent, up-to-date information. Updated reports, analytic content and dashboards are managed with centralized logins and permissions. Everything stays in sync, everyone stays on the same page. And that makes everybody happy.

Ready to take the next step toward getting the most value from your data? We offer several different technology, deployment and financing options, depending on your needs.

It’s here. It’s there. It’s everywhere. Get powerful insights and facts wherever and whenever they’re needed. With our BI tools, you can:

  • Stay in sync with fully native apps. Quickly and easily monitor and understand business performance. Native gestures and controls let you view and interact with dashboards, reports and charts – anywhere, anytime.
  • Explore to your heart’s content. Incorporate BI and analytics into a workflow or other app on mobile devices. Share insights with stakeholders to encourage wider discussions and greater collaboration.
  • Take it with you everywhere. The need to answer questions and make decisions doesn’t stop just because you’re not at your desk. Business users can can see and interact with key insights 24/7 – on their tablets or smartphones.
  • On-the-go access to current, relevant information. Having critical information at your fingertips means faster decision cycles and uninterrupted workflows. No delays.
  • Greater productivity and efficiency. Deliver static or interactive BI tools and analytic content – whatever the user needs – and meet a well-defined range of business demands.
  • The power of BI – magnified. Secure, feature-rich mobile apps give stakeholders the best user experience and flexibility possible.

Ready to take the next step toward getting the most value from your data? We offer several different technology, deployment and financing options, depending on your needs.