Many organizations have a false sense of confidence when it comes to databases and their vulnerability, believing that if their database is hit by a ransomware attack, it will automatically cease operations to indicate an attack has taken place. Then, they can just restore the last clean version of the database, and everything will be fine.
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The career paths of IT professionals—whether they start out as administrators, creatives, or executives—are as varied as snowflakes in a blizzard. Along the way, many of us are fortunate enough to meet mentors who guide us and help us grow into better professionals.
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At a time when every enterprise looks to leverage generative artificial intelligence, data sites are turning their attention to graph databases and knowledge graphs. The global graph database market size was $2.12 billion in 2022 and is expected to grow to $10.3 billion in 2032, according to estimates from Adroit Research. These databases enable data managers and analysts to model, store, and query complex and increasingly interconnected relationships between datapoints. They also are employed to construct knowledge graphs that can cut through data silos, enable semantic searches, and support chatbots and recommendation engines.
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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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