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From budgeting issues to buy-in challenges, data initiatives all too often fall short from the very start. Here’s how to overcome those hurdles and set your org up for success.
Business intelligence (BI) is a set of strategies and technologies for analyzing business information and transforming it into actionable insights that inform strategic and tactical business decisions.
Faced with increasing demands on his data engineering team, FiveStars CTO Matt Doka had a choice: drive for abstraction or be driven to distraction.
With marginal profits in an increasingly commoditised telecommunications market, Vodafone’s approach to growth lies in insourcing, a ‘mixed matrix’ team, and reusing engineering capabilities, says CDIO Scott Petty.
DataOps (data operations) brings together DevOps teams with data engineers and data scientists to provide the tools, processes, and skills to enable the data-driven enterprise.
Business intelligence (BI) enables companies to harness insights from massive amounts of data. But doing so requires overcoming a range of strategic and tactical challenges.
A strong, up-to-date data strategy is fundamental to your enterprise’s long-term success. In light of ongoing changes, it will probably need some serious updating.
Forward-thinking technology leaders are deploying a future-ready data strategy that can scale with demand and evolve with changing business requirements.
Decision support systems are a subset of business intelligence aimed at helping organizations make informed business decisions based on vast troves of analyzed data.
Organizations are accelerating their ability to make data-driven decisions by offering analytics capabilities directly to business users. Here’s how to do it right.