Darryl McKinnon, Vice President, South Asia & Korea, Teradata Corporation answers questions from Enterprise IT News about data and a cloud-first approach.
EITN: How has the pandemic changed the way organizations and teams work around data?
Darryl: The pandemic has changed the way organizations and business leaders think about data, particularly the role that it plays in a post-pandemic recovery and the importance of data in the overall business strategy.
According to a global survey that Teradata conducted, 90% of I.T. decision makers said that since the onset of COVID-19, the awareness of data’s importance in decision making has increased. In the financial sector for example, we are seeing more banks leveraging data to fortify customer relationships, delivering tailored financial services and products that meet the changing needs of their clients. The same changes can also be seen in the telco industry where more companies are now leveraging analytics to monitor service provisioning and anticipate anomalies in network traffic. This has helped telecommunications providers to optimize their networks in case of a sudden surge like the ones that happened during the onset of the pandemic.
While business leaders have always used data to glean better insights for decision-making purposes, the pandemic has further highlighted the significance of analyzing and sharing data with 94% of the executives surveyed agreeing that data is an essential asset and more importantly, key to the recovery.
We expect more business leaders to increase their focus on ensuring that data becomes a strategic asset to help organizations remain competitive and resilient in the new world that we live in.
We expect more business leaders to increase their focus on ensuring that data becomes a strategic asset to help organizations remain competitive and resilient in the new world that we live in.
EITN: How can businesses solve their existing data challenges through a cloud-first approach?
Darryl: The right cloud-first approach can help minimize, and in some cases even eliminate, existing data challenges. The variety of sources of data continues to increase from legacy applications to mobile devices and other machine-generated data. This makes it difficult and almost impossible to predict the required capacity. There are additional issues too – like the ones related to fluctuating storage and computing requirements as well as maintenance costs. In the cloud, there is no need to worry about capacity as organizations can scale up or down as needed.
As organizations collect, store and analyze increasing volumes of data, security also becomes a greater concern. As they struggle to control data access and secure data assets, organizations are ultimately left to determine how to ensure compliance and governance without compromising on agility and performance. Such challenges can be addressed in the cloud by choosing a data warehousing system that has robust controls in place to address both privacy and security concerns.
Lastly, budget limitations are often the biggest challenge that organizations face when it comes to managing their data. The growing volume, variety and speed at which data is being processed can result in unsustainable IT costs. In reality, organizations need to know how to get value from their data without breaking the bank. The need to scale and manage data while still reducing IT costs is very much needed in today’s business environment, and this is what the cloud enables organizations to do.
With the many cloud options presented to organizations, it is important to consider using a platform that delivers the flexibility and portability to deploy anywhere, both on multiple public clouds and on premise and while avoiding single vendor lock-in. For example, Teradata Vantage enables organizations to create a connected data analytics ecosystem and scale to support millions of interactions across the enterprise. This not only allows them to manage large volumes of data but also to optimize workload management in the cloud while controlling costs.
EITN: Please share top 3 outcomes from successful data management and data analytics
Darryl: For successful data management, organizations need to focus on three core areas where data really matters: improving decision making, improving operations and monetisation of data.
With the first, organizations are able to collect better market and customer intelligence. The second helps companies gain efficiencies and improve operations. And the third provides the opportunity for organizations to build data into their product offerings – thereby monetising the data itself.
To get the most value out of data management and data analytics, organizations must remember
that:
Data must be reusable. Store it once, use many times. This does not mean only store it in an expensive storage tier. It means only store it once in the ecosystem.
Data needs to be integrated so that more questions can be asked and deeper insights can be uncovered. Data in isolation delivers limited value. The true power of enterprise data comes from combining multiple sources and types of data to produce a broader view of the organization.
Data must also be scalable so question can be asked against any data and any time at scale. This is a problem for traditional analytics platforms that can only increase the scale of one dimension at the cost of another. A modern analytics platform on the other hand, provides multidimensional scalability that can enable each dimension to scale independently, giving users the flexibility to ask any question, at any time, unconstrained by technology.
Finally, organizations need to put their data to work to drive operational intelligence across the company. Creating value from data is more than just delivering “one-off” insights – it requires organizations to treat their data as its greatest asset and operationalize it.
Creating value from data is more than just delivering “one-off” insights – it requires organizations to treat their data as its greatest asset and operationalize it.
EITN: Have you put anything in place so that organizations that send their employees home can eliminate what seems to be exacerbated data siloes?
Darryl: The vast amount of data passing through organizations means that they are focused on identifying, acquiring, saving and using data, but not necessarily integrating it or sharing it broadly throughout various business units. This creates data siloes, hindering organizations from using such data to manage the business holistically. To that end, data must be seen and treated as a business asset.
With employees now operating from various devices, locations and networks, business leaders must ensure that data analytics ecosystems across functions, teams and the entire organizations are an integrated end-to-end system of systems.
Organizations need to move away from a siloed approach and adopt a unified approach with an answer-oriented model that will enable them to ask any question, against any data, at any time, without restrictions.
For example, Teradata Vantage is designed to bring down data silos in large organizations and provide a single comprehensive data strategy, bringing multiple data sources on one platform. This empowers users to access any data across the enterprise seamlessly, transparently, and at scale, using a broad set of open source and commercial technologies.
If yes, what is the level of investment required?
There is a certain level of investment required for organizations to eliminate data siloes and it starts with creating a long-term data strategy. As mentioned before, companies that survive and thrive are the ones that realize their data is a key asset and as a result, work on a strategy to operationalize it. This means making sure that their data is reusable, integrated, scalable and ultimately, making it work to drive operational intelligence across the company. As such, it is crucial to invest in a solution that can transcend the entire organization at hyperscale to support larger, more complex data sets. This will not only empower users but also accelerate decisions across the organization to help drive agility and innovation.
EITN: Are you future proofing for a future that may see permanent remote working?
Darryl: The pandemic has forced organizations to rely on virtual connectivity for business continuity. It is clear that collaboration has become a defining success factor for many functions and the wider organization, to emerge stronger.
An investment in modern data management technologies can allow organizations to pull together distributed data from various teams, ensuring that it can be analyzed and used to produce insights in real time.
An investment in modern data management technologies can allow organizations to pull together distributed data from various teams, ensuring that it can be analyzed and used to produce insights in real time.
Considering that various teams may use different tools and applications, organizations must also consider a solution that supports these common tools and languages and eliminates the need for data and analytics silos. That translates into users spending less time stitching together different solutions and more time finding and applying answers to the business’ most critical strategic questions.
