Some things don't change, even during a pandemic. Consistent with previous years, in CIO\u2019s\u00a02021 State of the CIO survey, a plurality of the 1,062 IT leaders surveyed chose \u201cdata\/business analytics\u201d as the No.1 tech initiative expected to drive IT investment.\nUnfortunately, analytics initiatives seldom do nearly as well when it comes to stakeholder satisfaction.\nLast year, CIO contributor Mary K. Pratt offered an excellent analysis of why data analytics initiatives still fail, including poor-quality or siloed data, vague rather than targeted business objectives, and clunky one-size-fits-all feature sets. But a number of fresh approaches and technologies are making these pratfalls less likely.\nIn this bundle of articles from CIO, Computerworld, CSO, InfoWorld, and Network World, you\u2019ll find advice and examples that can help ensure your own analytics efforts deliver the goods. These initiatives tend to resemble dev projects \u2013 even when commercial products are involved \u2013 and feature the same well-defined goals and iterative cycles that distinguish successful software development outcomes.\n\nTech Spotlight: Analytics\n\nAnalytics in the cloud: Key challenges and how to overcome them (CIO)\nCollaboration analytics: Yes, you can track employees. Should you? (Computerworld)\nHow data poisoning attacks corrupt machine learning models (CSO)\nHow to excel with data analytics (InfoWorld)\nMajor League Baseball makes a run at network visibility (Network World)\n\n\nTo get the big picture, start with the InfoWorld primer \u201cHow to excel with data analytics\u201d by contributor Bob Violino. In this crisply written piece, Violino covers all the bases: establishing analytics centers of excellence; the benefits of self-service solutions (such as Tableau or Power BI); the exciting possibilities for\u00a0machine learning; and the swing toward cloud analytics solutions. Violino expands on that last point in a second article, this one for CIO: \u201cAnalytics in the cloud: Key challenges and how to overcome them.\u201d As he observes, the cloud\u2019s scalability and abundant analytics tools may be irresistible, but migrating masses of company data to the cloud and securing it can be a heart-pounding adventure.\nNew technology invariably incurs new risks. No advancement has had more momentous impact on analytics than machine learning \u2013 from automating data prep to detecting meaningful patterns in data \u2013 but it also adds an unforeseen hazard. As CSO Senior Writer Lucian Constantin explains in "How data poisoning attacks corrupt machine learning models," deliberately skewed data injected by\u00a0malicious hackers can tilt models toward some nefarious goal. The result could be, say, manipulated product recommendations, or even the ability for hackers to infer confidential underlying data.\nWithout question, analytics has a dark side, as Matthew Finnegan corroborates in the Computerworld article \u201cCollaboration analytics: Yes, you can track employees. Should you?\u201d Collecting and analyzing metadata about user interactions on collaboration platforms has its legitimate benefits, such the ability to identify communication bottlenecks or to optimize the employee experience. But the same platforms can be used as employee monitoring systems that invade privacy and degrade trust between management and everyone else.\nOn a lighter note, consider this fine case study about analytics boosting user satisfaction: "Major League Baseball makes a run at network visibility." Writing for Network World, Senior Editor Ann Bednarz examines how MLB employs network flow analysis software across its infrastructure to ensure players and fans enjoy consistent network performance \u2013 end-to-end, from Wi-Fi in the seats to cloud services.\nThat effort to deploy unified network analytics to optimize the user experience began just two years ago, mainly because MLB's new\u00a0principal network automation software engineer saw the necessity. His realization broke through perhaps the most important barrier to successful analytics initiatives: cultural inertia.\nIn the end, the secret to successful analytics is not in choosing and implementing the perfect technology, but in cultivating a broad understanding that pervasive analytics yields better decisions and superior outcomes. Usually, you can iron out technology kinks or requirements misunderstandings. But if you can't change the mindset, few will use the beautiful analytics machine you just built.