Remove 2018 Remove Data Lake Remove IoT
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Havmor’s VP IT Dhaval Mankad on ‘melting’ hurdles with a scoop of digital innovation

CIO Business Intelligence

To add perspective, since I joined Havmor, the company has grown significantly, but not the workforce, having reduced by 30% compare to our numbers in 2018, thanks to digital innovation and transformation. What are some of the unique data and cybersecurity challenges that Havmor faces as a vast customer-centric business?

IT 98
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Interview with: Sankar Narayanan, Chief Practice Officer at Fractal Analytics

Corinium

Some of the work is very foundational, such as building an enterprise data lake and migrating it to the cloud, which enables other more direct value-added activities such as self-service. In the long run, we see a steep increase in the proliferation of all types of data due to IoT which will pose both challenges and opportunities.

Insurance 250
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My introduction and my love for DATA

Sanjeev Mohan

One area where I have lagged in is social media and I plan to be more active in this space in 2018. Somehow the data deluge barely leaves enough oxygen for a social media dopamine fix! Look forward to blogs spanning big data technologies, advanced analytics, data governance, IoT and blockchain.

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

BizAcuity

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. Microsoft starts to offer Azure IoT Central and IoT Edge. Google announces Cloud IoT.

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Three Trends for Modernizing Analytics and Data Warehousing in 2019

Cloudera

Business intelligence (BI), an umbrella term coined in 1989 by Howard Dresner, Chief Research Officer at Dresner Advisory Services, refers to the ability of end-users to access and analyze enterprise data. Only three years later, that number more than tripled to 59% in 2018.

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Australian data management discovery tour

Sanjeev Mohan

However, most data privacy discussions veered towards the EU GDPR ([link] which is now less than 100 days away from enforcement (May 25, 2018). Data warehouse modernization was a common theme followed by developing data lakes. Migrating to the cloud was very high on everyone’s priority.

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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.”.