With more and more use cases for AI and all its branches taking shape, big data is surging in relevance as the backbone of these projects—prompting DBAs, IT, data scientists, and more to take a closer look at the information being fed into their forecasts and models. To support organizations in navigating through new challenges and a rapidly evolving big data ecosystem, Big Data Quarterly presents 2024's "Big Data 75," a list of companies driving innovation and expanding what is possible in terms of collecting, storing, and extracting value from data.
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As companies measure the health and performance of their IT/cloud/application infrastructure and various data-in-motion streams such as metrics, events, logs, and traces, the number of monitoring tools grows, resulting in a complicated and overloaded observability stack. Kishore Gopalakrishna, co-founder and CEO at StarTree, believes unified observability platforms can solve these pain points by providing the flexibility, data autonomy, and extensibility offered by a disaggregated model.
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It has been a whirlwind time for data managers and their enterprises, and the innovations that are reshaping data operations aren't showing any signs of slowing down soon. AI and advanced analytics are changing the game, of course, as are a myriad of technologies now available to help manage and extract business value from the data flowing through organizations. Here is what industry experts tell BDQ they now see emerging and what we can expect in the months and years to come.
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We decided this Sourcebook was timely, given how enterprise AI has caught mainstream attention and triggered the imaginations of those working in IT, knowledge management, and a score of other areas within the enterprise. AI is dominating headlines, and people want to know how they can best apply the various technologies under the AI banner.
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