Remove 2016 Remove Data Lake Remove IoT
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MongoDB Enhances Developer Data Platform

David Menninger's Analyst Perspectives

While the company continues to make its software available for self-managed deployment on premises or in the cloud via MongoDB Enterprise Advanced and the MongoDB Community Edition free download, the proportion of MongoDBs revenue associated with Atlas has been steadily increasing since it was launched in 2016 and accounted for 71% of MongoDBs $478.1

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2016 Data Predictions from Gaurav Dhillon

In(tegrate) the Clouds

His predictions are as follows: Data Eats the World and Integration Strategies Will Drive Digital Transformation. Rising Data Lakes will Drown the Warehouse. IoT Goes from Over-Hyped to Emerging Reality. Multi-Cloud is the New Reality.

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A Few 2016 Technology Predictions

In(tegrate) the Clouds

I enjoy the end of the year technology predictions, even though it’s hard to argue with this tweet from Merv Adrian: By 2016, 99% of readers will be utterly sick of predictions. 2016 will be the year of the data lake. In 2016, which software company will be the biggest game-changer for the long term?

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Digital transformation: nei progetti a tutto campo la chiave è il change management

CIO Business Intelligence

“Il digitale è riconosciuto come forte leva di business”, conferma Alessandra Luksch, Direttore dell’Osservatorio Digital Transformation Academy e dell’Osservatorio Startup Thinking del Politecnico di Milano, che dal 2016 mappa i trend della spesa ICT delle organizzazioni in Italia.

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How The Cloud Made ‘Data-Driven Culture’ Possible | Part 1

BizAcuity

2016: Oracle launches with competencies across compute, storage, and networking. Google launches BigQuery, its own data warehousing tool and Microsoft introduces Azure SQL Data Warehouse and Azure Data Lake Store. 2018: IoT and edge computing open up new opportunities for organizations. billion by 2025.

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Big Data Fabric Weaves Together Automation, Scalability, and Intelligence

Cloudera

Forrester describes Big Data Fabric as, “A unified, trusted, and comprehensive view of business data produced by orchestrating data sources automatically, intelligently, and securely, then preparing and processing them in big data platforms such as Hadoop and Apache Spark, data lakes, in-memory, and NoSQL.”.