Four trends that will shape data strategy in 2021
FYI, this story is more than a year old
Article by Cloudera field CTO for APJ Daniel Hand.
For many, the end of 2020 cannot come fast enough. However, if there is one thing that this year has taught us, it is that the world is moving faster, and businesses need to be agile and prepared to move more quickly when responding to threats and opportunities that define their future. And this perpetual state of readiness isn’t changing anytime soon.
At the heart of successful optimal response time is data modernisation enabling businesses to make better sense of their data, at speed and need. To do this, more entities are making the move from legacy mainframe databases to the cloud, either on-prem or a hybrid model.
This accelerated cloud adoption is enabling critical business decisions to be made faster and with even greater accuracy, thanks to robust data.
Many organisations in APAC have leveraged data to strengthen their business resilience in the past 12 months. The next step is to use data to gain the agility needed to address disruptive events in the future.
To do so, data strategies should address these four trends.
Hybrid cloud is set to become the default choice for most organisations. IDC predicts that by 2021, over 90% of enterprises in APAC (excluding Japan) will rely on a mix of on-premises/dedicated private cloud, several public clouds, and legacy platforms to meet their infrastructure needs.
With data spread across the hybrid cloud, it is vital for organisations to effectively secure and govern their data regardless of where it resides or is used. Businesses that lack robust security and governance systems not only risk being vulnerable to cyber-attacks and insider threats, they’ll also struggle to comply with regulations such as data privacy laws.
Forward-thinking APAC organisations have countered these challenges by using an enterprise data cloud that can enforce a consistent set of security and governance policies across hybrid cloud environments — including fine-grained access controls, data lineage, and audit logs.
Case in point: Banks that have done so are better able to comply with anti-money laundering regulations. By having visibility of their entire data lifecycle, they can easily demonstrate to regulators that they are using complete and accurate data to monitor money laundering activities.
To address the increasing number of cyber-attacks and data privacy concerns, more organisations should focus on ensuring their data platform can provide consistent data security, governance, lineage, and control across their hybrid cloud next year.
As organisations digitally transform, they will be faced with exponentially growing amounts of data and increasing complexities of new technologies.
More businesses are turning to machine learning to overcome those challenges. Some APAC telcos, for instance, are starting to explore how machine learning can help them manage their networks and better predict workloads to ensure their services are consistent and reliable.
Despite increased interest in the technology, many organisations are taking a piecemeal approach to machine learning, hindering them from becoming truly data-driven. APAC organisations can overcome this by operationalising machine learning.
This requires them to understand, trust, and communicate a machine learning model’s ability to impact the business meaningfully. Those that can do so will be well-poised to survive and thrive in the next normal.
APAC appears to be leading the global 5G race, but the level of readiness varies between countries. While China and South Korea are seeing strong growth towards offering nationwide 5G mobile coverage, many markets like Australia, Japan, and Singapore are in the midst of rolling out 5G networks.
However, more telecommunications providers (telcos) in the region are starting or continuing to upgrade their current networks to deliver the high-speed, low latency and more reliable connectivity that 5G can offer. In fact, emerging markets or new telcos may outpace developed countries and established telco players in the 5G race as they can leapfrog to the latest system instead of overhauling their existing infrastructure.
The rise of 5G will impact an organisation’s data strategy, as the technology can provide massive connectivity for the Internet of Things (IoT), despite A/NZ’s size and distance, bringing insight closer to reach than ever before.
Since a 5G network can handle up to one million connected devices over one square kilometre, APAC organisations embracing IoT must be prepared to navigate the data storm created by those connected devices.
They can do so by using an enterprise data cloud which enables them to effectively capture IoT data and quickly analyse it on its own or with data from other sources, such as a data warehouse or data lake. This will enable the delivery of meaningful insights while protecting data at every stage of the data lifecycle.
As more companies use AI to create scalable solutions, the move also increases reputational, regulatory, and legal risks.
Since AI systems learn from the datasets they are trained with, APAC must tackle the ethical problems that arise from the widespread collection, analysis, and use of massive amounts of data.
Today, ethical AI conversations revolve around the anonymisation of data. While Australia, Singapore, and South Korea already have AI frameworks in place, other markets, including India and Indonesia, will continue to create regulations and set national standards for AI innovation in 2021.
Besides that, APAC organisations can do their part by having strong data governance. Consider using enterprise data cloud to simplify governance and address the lack of transparency around the data models and information infrastructures used to power AI systems.
Data is no doubt a strategic asset that can help organisations gain the agility needed to navigate through the uncertainties 2021 and beyond may present. However, the rising importance of data and increasing usage of new technologies such as AI will create new challenges.
This makes it critical that an enterprise data cloud supports data strategies to enable future business requirements and provide every employee access to data to effectively deliver for customers and business.
Enterprise data clouds can also help control costs, reduce risks, and enforce consistent security and governance across all data assets. By making data ‘known’, or discoverable, available, trusted, and compliant, organisations will be in a better position to improve operational efficiency, find new revenue streams, and deliver better customer experience or services even in the face of disruption.