How CIOs can create data centric digital strategies

BrandPost By Oracle
Aug 06, 2020
IT Leadership

data analytics / risk assessment / tracking data or trends
Credit: ipopba / Getty Images

In the hit TV series, Game of Thrones, “winter is coming” was an ominous threat gnawing at every character as the series inched towards its conclusion.

But in the world of Big Data and artificial intelligence (AI), the world is just emerging from a 59-year “winter”, according to Oracle Asia-Pacific and Japan, Senior Vice-President, Systems, Alliances, Channels, and ISV, Han Chung Heng.

“AI and machine learning has been around for more than 60 years. But 59 of those years were what we consider as AI “winter” – it is really only in 2020 that we have started to see AI scaling,” Han says.

(Podcast player not loading? Click here to listen to the episode on Spotify or iTunes)

Speaking on episode 2 of CIO Asia’s Data in the Digital Age podcast series, Han talked about the formula needed to achieve the level of successful data management for high performance AI.

“There are about 67 stages to completing a successful data management system,” he says. “It begins with data discovery, moves through data coming from events, Internet of Things (IoT), devices, sensors, and social media. Then it must be ingested, transformed and loaded into the system. We are also seeing the next generation of data flowing directly off the web, so organizations must have tools capable of ingesting and parsing that.”

In the podcast, Han also talks about the other key stages CIOs must be aware of for success in data management.

Key steps in building a data management framework include:

  • Building capability to manage data technology across multiple hybrid Cloud environments.
  • Unifying data across multiple types and sources.
  • Applying data protection and security.
  • Implementing a strong governance program that takes into account ethical and privacy considerations.
  • Staying across new technology innovations to ensure data assets are fully leveraged.

One of the keys to this success is modernizing the approach to processing data, bringing algorithms into the data lake, rather than trying to export the data out to the algorithms, Han says.

“CIOs should look to run algorithms close to the data. It allows data processing much faster than data going in search of the compute and algorithm,” he says.

Data must also be highly available, so when employees need it they can immediately access it. “If you have a hundred transactions running per minute, but the data lake is not available to be analyzed, how much revenue will be potentially lost?” Han says.

“One of the things we do well at Oracle is a product called Exadata. It has been designed using the Intel Optane DC persistent memory chip which allows for very high performance including the most demanding workloads and availability, and unifies all data into a single platform,” he says.

A major airline using these techniques is case-studied in the podcast. The airline has been quietly investing in data strategies since the early 2000s and now has a mammoth data processing operation, driving all parts of its business. It has since launched a “data labs” to drive further data-crunching innovation in its business.

In this episode of CIO Asia’s Data in the Digital Age podcast, we discuss the formula for long-lasting data management strategies for successful digital transformation, and look at specific strategies CIOs can take to optimize data processing systems.

Don’t miss out on episode 1 of CIO Asia’s Data in the Digital Age podcast. Click here to listen.