Strategic advice to leverage new technologies
Technology is at the heart of nearly every enterprise, enabling new business models and strategies, and serving as the catalyst to industry convergence. Leveraging the right technology can improve business outcomes, providing intelligence and insights that help you make more informed and accurate decisions. From finding patterns in data through data science, to curating relevant insights with data analytics, to the predictive abilities and innumerable applications of AI, to solving challenging business problems with ML, NLP, and knowledge graphs, technology has brought decision-making to a more intelligent level. Keep pace with the technology trends, opportunities, applications, and real-world use cases that will move your organization closer to its transformation and business goals.
Insight
There are two components to post-project evaluations that focus on two related areas: how well the project was executed and what was the business impact it created. This second Advisor in a series of three articles on post-project evaluations takes a closer look at the first area, assessing project performance.
Content managing has only recently been recognized as a profession. And through the growth of the Internet, the need for content management has become increasingly important. The catch is that very few people know how to do it well. It's not that the technology is poor or that we lack processes for implementation and ongoing management of content management systems (CMS); rather, it's a lack of people with the right level of understanding to do the job.
Recently, the US National Counterterrorism Center (NCC) revealed that its database containing approximately 325,000 names of alleged international terrorist suspects (or people suspected of helping them) is actually inflated by about 135,000 extra names. This revelation serves to highlight a problem that many organizations of all sizes and focus struggle to deal with: duplicate customer names and records.
In my last Trends Advisor ("Real Enterprise Data Architecture, Part 1," 23 February 2006), I touched on the issue of enterprise data architecture from a conceptual standpoint. I suggested that being an enterprise data architect (as opposed to a DBA or data modeler) demands that you take a very high-level view of the company.
Scrum is probably the most popular agile method right now in the USA. The power of Scrum is its simplicity. There are only a handful of Scrum rules and so it is easy to get a team started with Scrum [1]. And yet Scrum can unleash the potential of a team and dramatically improve its productivity within weeks. A Scrum team works on one project at a time and Scrum provides a toolkit to cut through complexity so that everyone can focus on doing their job rather than fending off multiple drains on their time.
Vendors today are introducing new products that apply advanced algorithms designed specifically for e-mail analysis. The result is an emerging market: e-mail intelligence.