Augmenting BI and Analytics in the Age of AI and Big Data

Arcadia Data

Artificial intelligence (AI) and big data technologies are driving major changes in how organizations think about business intelligence and analytics. Rather than be limited to querying and reporting on just what is in traditional BI systems or data warehouses, many business users and analysts want to tap a fuller range of data in systems running Apache Hadoop, Apache Spark, or on cloud data platforms and storage. At the same time, AI practices and technologies (in particular machine learning and natural language processing) are changing how users explore, analyze, and interact with data and the types of insights they can generate.
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Spotlight

Enterprises are rapidly discovering the power of Apache Hadoop and big data to drive more powerful, data-driven insights and better position their organizations in an increasingly dynamic and competitive economy. Hadoop’s innovation in scalability, cost efficiency, and flexibility affords enterprises an unprecedented ability to handle greater volume, greater velocity, and greater variety of data than traditional data management technologies. For these information-driven enterprises, this next step in the evolution of data management is an enterprise data hub.

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Data Strategy Best Practices

infogix

Your Data Strategy should be concise, actionable, and understandable by business and IT! Data is not just another resource. It is your most powerful, yet poorly managed and therefore underutilized organizational asset. Data are your sole non-depletable, non-degradable, durable strategic assets, and they are pervasively shared across every organizational area. Overcoming lack of talent, barriers in organizational thinking, and seven specific data sins are organizational prerequisites to be satisfied before (a measurable) nine out of 10 organizations can achieve the three primary goals of an organizational Data Strategy, which are to:
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How to advance your Data Analytics Maturity: Key steps to take you to the next level

Today’s most successful organisations are utilising data to drive accelerated growth. They are each on a journey towards greater data maturity, increasing the value of their data and deepening their insights as they go. However, the rapid growth of analytic solutions has not successfully transformed every business into a data-driven powerhouse – yet. So how can you ensure the route you take to AI maturity is a successful one? As with any endeavor, your company will face obstacles as you strive to transform into a data-driven organisation. To succeed, it’s important to evaluate where you are today, the challenges that lie ahead, and what exactly “ahead” means for you and your team.
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Oracle Autonomous Database - Keep Data More Secured, Eliminate Costly Data Breaches

Oracle

Data, the life blood of today's economy, is an attractive target for cyber attackers. Learn how a self-securing database provides security and peace of mind without relying on manual, error-prone processes allowing you to focus on innovation and not damage control.
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Forrester Research: The State of Enterprise CRM Data Management 2021

The results are in! Over the summer of 2021, Odaseva and Forrester collaborated on a survey studying how CRM professionals in large enterprises feel about their ability to manage data, the challenges they are facing, and the emerging trends impacting their success. The responses were eye-opening.
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Spotlight

Enterprises are rapidly discovering the power of Apache Hadoop and big data to drive more powerful, data-driven insights and better position their organizations in an increasingly dynamic and competitive economy. Hadoop’s innovation in scalability, cost efficiency, and flexibility affords enterprises an unprecedented ability to handle greater volume, greater velocity, and greater variety of data than traditional data management technologies. For these information-driven enterprises, this next step in the evolution of data management is an enterprise data hub.

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