Tag: data analytics

ICTP 268: Optimising performance and success through business intelligence, with Raquel Seville of BI Brainz

ICTP 268: Optimising performance and success through business intelligence, with Raquel Seville of BI Brainz

Posted by | 6 Sep 2023 |

Business intelligence (BI), like data analytics, does not seem to be as prominent these days as data science and Artificial Intelligence (AI). However, data analytics and BI are separate disciplines from data science and AI, with the former still being especially relevant when trying to improve organisational performance and success. With Raquel Seville of BI Brainz, we get a primer on BI, and among other things, she highlights: misconceptions people have about BI; important skills individuals who want to work in BI should possess; and basic activities and tools MSMEs can use to begin to tap into the benefits of BI.

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ICTP 242:  Breaking the glass ceiling in Data Science

ICTP 242:  Breaking the glass ceiling in Data Science

Posted by | 8 Mar 2023 |

In recognition of International Women’s Day, and with Dr Letetia Addison, Shannon-Rae Hackett and Riana Kandhai of the University of the West Indies, St Augustine campus and Women in Data Science (WiDS), the Trinidad and Tobago chapter, they discuss, among other things: the difference between data analytics and data science; their own journeys to pursue careers in the STEM and ICT fields, and how their perspective on the career has evolved; and why organisations have been dragging their feet to integrate data science/data analytics into their operations.

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ICTP 229: Moving from data to insights, with Liselle Ramcharan-Briscoe

ICTP 229: Moving from data to insights, with Liselle Ramcharan-Briscoe

Posted by | 9 Nov 2022 |

Information Management professional, Liselle Ramcharan-Briscoe, discusses among other things: the types of data that could benefit from a data warehousing solution; when an organisation should consider moving to a data warehouse configuration; privacy and data protection issues that still must be considered; and why more organisations may actually need a data warehouse.

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