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Oracle Exadata: World’s Fastest Database Machine
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5 Steps to Ensure the Success of Your Cloud Data Migration
Moving from on-premises data environments to the cloud is an incredibly complex and technical challenge. In fact, a report from Cloud Security Alliance finds that 90% of CIOs have encountered failed or disrupted data migration initiatives.
How can organizations ensure they create tangible business value with a cloud data warehouse?
It all starts with a plan. Business leaders need to map out a strategy and plan what to migrate, how to migrate it, and when to migrate it to maximize their investment in the cloud.
Read on for an in-depth look at 5 steps to leading a successful cloud migration, including:
- Analysis and disposition
- Initial migration
- Revise and test dependent assets
- And 2 more
These are also closely related to: "Oracle Exadata: World’s Fastest Database Machine"
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Jargon buster guide to database management
Database management roles have long been a rich career seam for IT professionals. However, there has been, in recent years, a “Cambrian explosion” in the previously steady but sleepy world of databases.
The relational database model, breaking the traditional dependency between data storage and applications, held sway in enterprise IT for decades, from the time of its serious commercialisation by Oracle in the mid-7os. Also hegemonic has been the language implementation of the relational model, SQL – Structured Query Language; which is of the same mid-70s vintage.
But, in recent years, with the rise of the big data technologies of the Hadoop stack and the NoSQL databases, the data store and database scene has become more complex.
And when it comes to the Oracle database, its creator announced it to be “autonomous” at Oracle Open World in San Francisco October 2017. What does this mean for database administrators (DBAs)? Does it mean the opening up of new roles of higher intellectual interest and value? Or does it mean redundancy and early retirement?
As always with IT, the technology is only one-third of the story – the others being process and, crucially, people. What are the operational and organisational design problems to be solved in this more heterogenous database management landscape?
This Jargon Buster e-guide to contemporary database management is an aid to stepping back and thinking afresh about an area of enterprise IT that has many decades of heritage. Or, as many sometimes (arguably rudely) put it, legacy.
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Oracle - Autonomous computing that declines a special name
Oracle has chosen not to name its artificial intelligence efforts after a genius departed, like Einstein, Leonardo, Watson, or Coleman. This does not mean it has refrained from baking AI, especially machine learning, into its database and applications.
Far from it. Larry Ellison, the company’s founder and chief technology officer, declared the Oracle database “autonomous” – and revolutionary – last year and co-CEO Mark Hurd has been stressing the machine learning being added to the vendor’s applications since then, too.
Allied to the turn to autonomisation has been the firm’s march to the cloud, which has been steady and, despite financial analyst concerns that the revenue from it has been obscured, ostensibly serious in intent.
From this e-guide you can follow Oracle’s twin paths to adding AI and delivering its software over the cloud – on its own platform and infrastructure as a service, from 2017 to 2018.
An over-arching theme of Oracle’s case regarding its infusion of machine learning and its declared re-architecting of its cloud delivery has been security, security, security.
