Spreadsheets are excellent tools as far as they go—but how far can they truly go? If you’re pushing your spreadsheet-based solutions beyond their viable limits, then they might be doing more harm than good. Discover what considerations you shouldn’t ignore when using spreadsheets for statistical
Many avenues can be explored at IBM Insight at World of Watson 2016. See what one observer came away with after attending several sessions devoted to the CDO and collaboration, tools and strategy within the CDO domain.
From self-service analytics to the cloud, chief data officers (CDOs) had a wealth of information at their fingertips on the first day of IBM Insight at World of Watson 2016. Catch the high points of some of Monday’s most relevant sessions for CDOs in this quick recap.
Data analytics is no longer an either/or choice. With the integration of IBM SPSS Statistics and R, you can bring together the statistical analysis and data management capabilities that have helped so many data scientists gain insight after insight from their data.
Data is widely seen as the new source of competitive advantage, driving smarter decisions and helping enterprises outthink their rivals. But opportunities are often missed. Getting the data needed from multiple underlying systems can take far too long for application developers, business analysts
Apache Spark, sometimes called the “analytics operating system,” is empowering organizations of all kinds through machine learning by helping them create unprecedented value from their data. Discover eight ways that Apache Spark’s machine learning capabilities are driving the modern business.
Historical application of vector mathematics and the study of unstructured text data can be an important approach to understanding and actualizing the value of data. See how mathematical exploration of text data can unearth insight that translates into enhanced decision making.
Hear from Nancy Hensley, director of offering management for IBM Analytics who speaks with Rob Thomas, VP of development for analytics on the subject of business transformation and a discussion of the data maturity curve.
Nancy Hensley, director of offering management for IBM Analytics speaks with Rob Thomas, vice president of development for analytics, at IBM, on the subject of business transformation, leading to a discussion of the data maturity curve.
Many marketing concerns have seen the light when it comes to the application of big data analysis as a means of outthinking the competition. Discover three best practices for implementing big data analytics for good data science in marketing initiatives.
Has your business adopted a hybrid analytics architecture as part of its quest to compete? Listen as Martin Fleming, IBM’s chief analytics officer and chief economist, explains why doing data analytics on the cloud is creating opportunities for modern businesses, and be sure to take notes as he
Inderpal Bhandari, chief global data officer at IBM, talks about the many nuances of data, value of analytics and importance of the partnership between the CIO office and CDO office. He also discusses why building a comprehensive data strategy is important for organizations. Check out this CIO
Developers and data engineers’ horizons are broadening with the advent of technologies designed to help them build and deploy analytics applications quickly and easily. Take part in the open beta of the Basic Plan for IBM BigInsights on Cloud to find out what lies in your future as you build