Plan your data management strategy

Forrester research identified five cornerstones around which any data management strategy should be built. We explore what this means in an increasingly complex and multicloud IT environment.

1 The current outlook

2 Managing your data

3 Unifying your data

4 Securing your data

5 Governing your data

6 Optimising your data

1. The current outlook

Data strategy has had to adapt to the evolving complexity of IT environments, however, this continuing complexity makes data strategy harder to define and therefore execute.

Delivering increasingly personalised customer services and experiences is a key competitive differentiator. If you think of an enterprise as a living body, the data is certainly the lifeblood. For businesses to successfully grow, they need to establish digital strategies built on the foundation of this precious resource.

Over time, IT estates have grown in complexity. As new technological capabilities became available within different lines of business, a variety of unique configurations emerged. IT teams continue to face the pressure of providing access to the tools and information people need to do their jobs, and organisations need to gain a competitive edge and deliver better customer experiences.

Line-of-business functions have therefore matured at different speeds and adopted different technologies. So depending on the cloud and data centre models available at the time of adoption, companies have a patchwork of different hardware, software, practices, and policies within their organisation. Integrating new hardware from one department with a legacy system in another—at scale—can be fraught with difficulty.

For a lot of organisations this has resulted in not just a hybrid architecture, but a multicloud environment. Within a single company, data management and protection practices can vary across line-of-business functions and departments. And while there are good reasons for each configuration being the way it is, this variety multiplies the challenges of attempting to securely and effectively utilise data in these environments.

As the importance of deriving actionable insight from information intensifies, what should businesses with a multicloud IT estate do to modify their data infrastructure?

For 40 years, Oracle has attained a deep understanding of data management, and we know that no two businesses are the same. So to get a grasp of how organisations are navigating this multicloud world, we commissioned Forrester to evaluate the current state of data management strategies.

The resulting research paper identified five cornerstones around which any data management strategy should be built:

  • Managing data technology across multicloud deployments
  • Unifying data across types and sources
  • Protecting and securing data
  • Ensuring data governance, ethics, and privacy
  • Leveraging technology innovation

Given the expediency with which much of the world has had to manage a wholesale adoption of remote working practices in response to the recent global health crisis, understanding and controlling data management has taken on a far greater urgency. In this ebook we explore each of these cornerstones and discuss their importance. We also explore how organisations can ensure they implement each of them swiftly, securely, and at scale.

2. Managing your data

Collect, consolidate, store, and analyse data seamlessly across multiple systems and multivendor cloud deployments.

Of the five cornerstones identified in the Forrester report, multicloud data management had the lowest maturity among the organisations surveyed. It's clear that these organisations are still in the stage of developing and scaling their capabilities to derive business value from their multicloud infrastructures.

But why are they lagging in this area?

Businesses are incrementally expanding their horizons to capture and use new types of data. Whether from different internal departments, third parties, IoT devices, or social platforms, the diversity of information available has never been greater—and it’s only going to increase. But while that presents a huge opportunity, it also presents a problem.

As they gather information in various forms from a range of sources, many businesses are suffering from ‘data friction’. They are struggling to achieve a clean and efficient data pipeline to flow between the different parts of their business.

Databases were typically built on premises, but as new waves of cloud applications became available for specific line-of-business functions, certain elements were moved to the cloud, and various hybrid environments emerged. Businesses had the luxury of picking and choosing 'best-of-breed' applications for individual use cases.

As the departments and functions across the business charted their own paths of application migration and data management, the multicloud model emerged.

But having disparate and fragmented data causes friction each time it is pulled in and out from applications. And although the multicloud model may be here to stay, this friction must be addressed given how data strategies are inextricably tied to the commercial success of a business.

The Oracle approach: removing the friction

Nearly two-thirds of organisations surveyed by Forrester said they were prioritising their ability to manage data across systems and deployment options. The challenge they face lies in finding a way to seamlessly flow data from the source through the pipeline to analysis in real time, while preserving data quality and accommodating the many disparate data types and environments.

To solve the data friction caused by multicloud deployments, enterprises must find an agile, cloud-agnostic solution. That solution needs to be able to collect, consolidate, store, and analyse data seamlessly across multiple systems and multivendor cloud deployments, all while reducing the reliance on physical access on premises.

Oracle technologies all work in the cloud and on premises, and they offer additional flexibility through our partnership with Microsoft, as well as compatibility with other third-party suppliers such as AWS. The colocation capability, coupled with key cloud-agnostic technologies that were built specifically for Oracle Database—such as Oracle Recovery Manager, Oracle Data Guard, and Oracle GoldenGate—help you manage your data across multiple providers as well as in your own data centre.

To learn how to optimise, secure, and enhance the way your organization processes critical data, click here.

3. Unifying your data

Moving to a converged data platform lets you store and combine data from different sources for richer analysis, without the need to move it from its original location.

Enterprises today are collecting data from a wide variety of sources. Each new source adds more context and insight to the existing mass of data. When combined, analysed, and used in the right way, this data holds the key to creating a 720-degree view of customers and enables businesses to craft better, more-personalised experiences.

According to the Forrester report, organisations are working to make the best of their diverse data sources: 70% believe that their business strategy articulates how their firm will use data for competitive differentiation.

However, as the data volume, variety, and velocity increases, data becomes more difficult to manage. The report goes on to assert that ‘data unification is the foundational pillar that decision-makers need to start with when building their data management architecture’.

Traditionally, enterprises have followed a process of extracting data and then moving it to a tool or platform for analysis or for creating models. But having to move duplicate data from one environment to another is neither efficient nor secure. The more you move data between platforms, the greater the risk of data loss, theft, fragmentation, or corruption.

Moving data in this way also makes it harder to ensure consistency and uniformity across your estate because there is no single source of the truth anymore. There are also the ever-expanding storage and security requirements to contend with. Each time you run any sort of analysis or apply machine learning (ML) to a dataset, you are creating yet more data.

In addition, analysts use a variety of analytical tools and servers to create models based on the data extracts. Once the models have been created, IT must then figure out the deployment process and application integration issues. Having separate ‘islands’ for data management and data science prevents organisations from getting the most out of their data and puts their data at risk.

Managing and sorting through the various data sources is the most important aspect. To do anything with the data, we need to be able to organize it.” CIO, Multinational conglomerate, India

The Oracle approach: converged data platforms

Enterprises are acutely aware of the value of their data and are starting to leverage ML algorithms and create AI models using all the data at their disposal. But the current methods of collecting, analysing, and acting on the insights are inefficient and unsecure. The solution is to move to a converged data platform—one that eliminates the traditional extract, move, load, analyse, export, move, load paradigm.

For decades, Oracle has been leading the way in converged data, and this evolution continues with Oracle Converged Database. It lets you store and combine a variety of data—special, graph, XML, JSON, row, and columnar—for richer analysis, without the need to move it from its original location.

In addition to storing a variety of data types in your own database, you may need access to third-party data sources, such as streaming or social media data. Oracle simplifies access to all data—both internal and publicly available—by creating a unified data platform. Oracle Big Data SQL creates this data virtualisation layer, so you can work with all data as if it were in the same location. This single point of access to the data is enabled without compromising performance due to the technology underpinning the platform.

The objective of storing and accessing all this data is to extract valuable insights and create ML models for prediction. Oracle embeds ML algorithms in the database itself, eliminating the need to move data to specific ML tools. By adopting a design that moves the algorithms to the data—rather than moving the data to the algorithms—you can remove many of the complexities and restrictions of a multicloud estate.

To explore how engineered systems can take infrastructure optimisation to the next level, click here.

4. Securing your data

Protect data at its source by building layers of security around it—from encryption to redaction, and from access to auditing.

Industry-governing bodies and government regulations such as GDPR are cracking down on data privacy and protection. Businesses that fail to take adequate IT security measures not only run the operational and commercial risk of downtime and system failures, but also face heavy penalties from regulators.

Half of respondents in the Forrester report said they currently lack the ability to adequately adhere to data protection regulations. This could be because many organisations have traditionally concentrated mainly on perimeter security.

With a multicloud environment that’s been built over time, ringfencing everything with a single line of defence might appear to be the easiest solution. The problem is, once there is any form of breach, the entire data estate is compromised.

It’s also worth remembering that 80% of data loss is caused by insiders. With the current proliferation of remote working—which is likely to continue for some time—everyone is now working in an unsecure environment.

The other side of the coin is data availability. Your security needs to be tight but breathable. If your teams and departments can’t access information in a timely manner, your business cannot reap the rewards. This is another problem with ringfencing. If you have data constantly moving between multiple applications, each with their own unique hybrid environments, every time the barrier is crossed it opens a point of weakness and expands the attack surface.

The #1 factor is security to ensure that data is not breached. Systems are assuming the level of security needed for the most exposed and hackable one.” CIO, Regional conglomerate, Malaysia

The Oracle approach: protection at every layer

The best way of securing data is to protect it where it resides so that access can be governed from any location, tool, or application. This calls for a ‘defence in depth’ approach to data, and Oracle has been at the forefront of data security since it was founded.

Only those with the appropriate access level can read the data, and access policies are easily managed with Oracle Database Vault, which also provides change control notifications. Oracle Database Vault can permit access based on ID, time, and location, and SQL only allows certain queries at certain times. Security and data protection policies are applied to all data types in one action, rather than having to manually configure them across each hybrid environment.

Accidents and outages can happen, however, and that’s why Oracle Maximum Availability Architecture works with Zero Data Loss Recovery Appliance to offer SLA compliance; fast, automated, and secure protection; and point-in-time recovery—so you can always access your data.

In addition to addressing data security, it's also important to examine the infrastructure hosting the data, which could be in the cloud or on premises. Oracle Cloud provides several features to secure data. On-premises deployments—as with Oracle Exadata—provide several layers of security. Starting with a secure firmware, the operating system has been optimised with only the necessary packages—reducing the surface attack area—and network segregation separates user access to data. Oracle Database security is an added layer on top of this.

Organisations need to protect data at its source. We start with the data in mind and build layers of security around it—from encryption to redaction, and from access to auditing—with availability built in at every layer.

To read more about recovering your business-critical data with effortless integrated security, click here.

5. Governing your data

A single foundation model can provide secure access with role-based controls, enabling greater protection and offering uniformity of access techniques for all data—as well as bolstering privacy.

As well as protecting your IT estate from external theft or corruption, you need to ensure that robust governance, ethics, and privacy policies are in place to guide how data is handled and managed within your organisation. The Forrester report revealed that 68% of organisations recognise the need for proper governance as they scale their use of data.

Because so many organisations are still moving their data through complicated multicloud systems and via multiple handlers en route to being analysed, its quality and integrity can be affected.

Imagine your data as a ball of soft clay. If you pass it down a line of 10 people, by the time it reaches the final person, its shape won’t quite be the same as when it left the first person’s hands. With each hybrid system having subtly different configurations and processes, the act of moving or analysing data can easily lead to it being mishandled, modified, duplicated, or deleted without anyone realising. This has the potential to make company data essentially useless. If an end user cannot verify the source or the accuracy of the data, trust in the system will erode.

Beyond the IT side of things, you'll need to make sure that your staff is adequately trained in how to effectively and compliantly use data. Everyone in the organisation should have a stake in the data. If individuals and teams aren’t up to speed on how to handle, store, share, and use certain types of data within company systems, you will struggle to ensure regulations such as GDPR are adhered to. Failure to comply can result in huge monetary fines, not to mention the lasting effects that brand damage and loss of trust can have on your business.

The Oracle approach: compliance and literacy

Oracle provides the tools and data-literacy processes that allow you to govern the data policies across your business and report on data quality.

A single foundation model—such as Oracle Database Vault—can provide secure access with role-based controls to limit who can access the source data, and Oracle Audit Vault provides full audit capabilities of the database for governance purposes. This enables greater protection and offers uniformity of access techniques for all data, as well as bolstering privacy.

We’re continuously working with regulators and auditors to build solutions and certifications for common criteria, including regulations regarding the use of personally identifiable information (PII). We also strengthen privacy by enforcing encryption for all data in our cloud, or using our cloud model, Oracle Cloud@Customer.

Organisations must provide all data handlers with evidence of data lineage, accuracy, and integrity. A culture of data literacy should not only be encouraged throughout the organisation, it should be built into the tools that individuals use.

To learn how to enter the managed cloud space using Oracle Private Cloud Appliance, click here.

6. Optimising your data

Engineered systems help you to focus your efforts on using the latest technologies to extract the insights that will give your business a competitive edge.

For the many enterprises running multivendor systems, leveraging new technologies such as ML, AI, data virtualisation, and containerisation means seeking individual vendors for those technologies. It’s the only way to manage a multivendor ecosystem that incorporates the essential technologies for delivering competitive, data-driven services.

But it requires a significant level of multivendor management to collect, store, and analyse a variety of different data types from several different sources in a multicloud environment. And as we’ve seen, there’s also the matter of ensuring that the data remains protected and available.

This can become a huge task in itself. Organisations must handle agreements, patching, support, maintenance, and security with a number of different suppliers simultaneously. And as new types of data become available, incorporating them into your business means having to address all these issues individually again every time.

Cumulatively, this can limit the agility and the efficiency of any organisation, and hamper its ability to gain optimum value from its data. And in a world where data is the lifeblood of the business, blockages and shortness of supply can be fatal. Modernising infrastructure or moving to the cloud becomes an onerous and potentially risky undertaking.

The Oracle approach: engineered systems

By its very nature, a multicloud estate is built from different components. Oracle’s engineered systems are architected, integrated, tested, and optimised to work together. So you can choose from a range of systems that are coengineered with Oracle software for cloud-ready integration—giving you all the benefits of new technologies without multiplying overheads and slowing down performance.

Oracle Database does the hard work of unifying data from across your business. It’s flexible, too. Through cloud equivalence and colocation options, it can be configured to bring consistency to complicated multicloud estates. So it’s simple and secure to bring in multiple new data types—such as JSON, XML, blockchain—and apply graph data and advanced analytics within the multicloud environment.

Data centre virtualisation means you don’t have to manage the movement of data from one location to another whenever you want to run queries or analyses. Machine learning is built into the database, so you can simply move the algorithms to the data in a simpler, more secure way.

Its autonomous database capabilities use built-in AI to take care of patching, support, maintenance, and security, so you can modernise and adapt to new cloud principles at your own pace.

And with continual updates that are automatically managed, you can focus your efforts on using the latest technologies to extract the insights that will give your business a competitive edge by delivering more personalised and valuable customer experiences.

According to Forrester, the foundational steps for building a robust data management strategy centre around enabling simplicity and visibility for both IT and business processes. Moving away from a do-it-yourself approach to an engineered system with a trusted partner will allow organisations to significantly cut the number of vendors they have to deal with, and remove the risks involved with modernising their infrastructure and adapting to new cloud principles.

Oracle’s engineered systems provide core Oracle Database and applications services to many thousands of customers around the world. They can integrate multiple systems to create full-stack environments that are dramatically simpler, perform better, are more secure and easier to manage, and cost substantially less than traditional do-it-yourself solutions.

To find out how to bring modern technologies into your organisation and drive change in your business, click here.

If you would like to read the Forrester research paper, click here.