Data estates: the urban sprawl of the data world

The value of data does not lie in the possession of it, but in its organization and the speed with which it can be accessed through the data estate.

About the author

Alphonsa Neil

Sr. Data Analyst, Product Perfect

With an MBA (Finance & Marketing) Alphonsa Neil is a data analyst with experience in financial advisory services, investor relations, and project management.

Around 100 years ago, land was the capital that defined generational wealth, power, and success. Sprawling mansions surrounded by acres of manicured lawns were the centerpieces of these traditional estates. Today, a new type of estate has become a symbol of financial performance and profitability for businesses: The Data Estate.

"Data is the new oil. It's valuable, but if unrefined it cannot really be used. It has to be changed into gas, plastic, chemicals, etc to create a valuable entity that drives profitable activity; so must data be broken down, analyzed for it to have value." - Clive Humby, British mathematician and entrepreneur.

Data is invaluable. It’s the new key resource in today's data-rich ecosystem. The success of data estates is not only dependent on the size and sprawl of data but also on the speed and agility with which it can be accessed and organized. Cloud computing, AI, ML, field programmable gate arrays, and other advanced technologies are all being used to store, analyze and make decisions based on data.

The use of these tools has enabled businesses to extract more value from their data and gain insights that were previously impossible. AI and ML are particularly powerful tools that allow for the automation of many tasks, the identification of patterns and trends, and the prediction of future outcomes.

The use of microwave radiation conduits is an interesting development, as it allows for even faster data transfer than fiberoptic cables. This could be particularly useful in applications where speed is of the essence, such as high-frequency trading or autonomous driving.

Overall, the ability to effectively manage and use data is becoming increasingly important for businesses across all industries. Those that can harness the power of data and use it to make better decisions will be more competitive and successful in the long run. These days we have tools that in a baseball analogy, might be represented by a pitcher with the speed of a Nolan Ryan fastball, the intimidation of the Big Unit’s slider, and Greg Maddux’s exquisite control- all in one.

Modern Data Estate Framework for Analytics. Source: omnidata

But what is a data estate?

A data estate is essentially all the infrastructure that helps companies manage all of their corporate data systematically. This infrastructure can include on-premises data, cloud, or (more typically) a combination of both. The data estate includes all data sources, including databases, data warehouses, data lakes, and other data repositories. It also includes tools and technologies used to collect, store, process, and analyze data.

Organizations need to manage large volumes of data from various sources in order to make data-driven decisions. A data estate approach allows organizations to take a holistic view of their data assets. In short, the goal is to organize, secure, and make data available to the right people at the right time.

“There were 5 exabytes of information created between the dawn of civilization through 2003, but that much information is now created every two days.”
Eric Schmidt, Former Executive Chairman at Google

Data warehouses and data lakes

As the concept of the data estate originated began to evolve over the past several decades, two distinct platforms emerged in the form of data warehouses and data lakes. These terms provide convenient analogies for how data is stored in either structured (warehouse) or unstructured (lake) forms. These concepts, and the relationships between them, are important for would-be data estate proprietors to understand and apply.

The data warehouse

Many companies began their data estate construction project with a traditional data warehouse (DW). The data warehouse is a centralized repository of data integrated from a variety of sources, organized in a structured way that allows the data to be retrieved without undue delay.

As an integral part of a data estate, the data warehouse integrates with other systems, such as ETL (Extract, Transform, Load) tools, business intelligence platforms, and data governance frameworks. A data warehouse can enable organizations to manage their data more effectively and derive valuable insights that support decision-making. This helps organizations to unlock the full potential of their data estate and leverage it to drive business value.

Data lakes

A data lake is a centralized data repository that can store a multitude of data ranging from structured or semi-structured data to completely unstructured data. Data can arrive at the data lake in any raw format to be stored for future processing and analysis. A data lake can be established on premises using local data center hardware, or in the cloud. Hyperscalers including Amazon, Microsoft, or Google offer customers 3rd party data lake solutions to minimize their own infrastructure and initial expense. Data lakes are known as a source of cost-effective yet near-infinite data storage.

Modern database management technologies and their applications in power grid database management. Source: Reasearchgate

Lakes, warehouses, and the cloud

Data lakes and data warehouses work together by providing complementary storage and management solutions for structured and unstructured data. While data lakes are often used for exploratory analytics and data discovery, data warehouses, with data stored in an optimized format for querying and analysis, are used for business intelligence and reporting. Data lakes can provide a flexible and scalable storage layer for diverse data types, while data warehouses can transform and structure the data from the data lakes.

Although data lakes and warehouses are perceived as slow IT platforms that contribute to data sprawl, cloud computing and virtualization added to the mix can overcome many inherent weaknesses of legacy architecture by consolidating data into less locations, providing more elasticity to prevent over-provisioning of resources, and applying higher levels of automation to reduce the need for manual intervention. These advantages have made hybrid solutions a popular approach to data estate modernization.

Who needs a data estate?

In today's data-driven economy, a well-managed data estate is increasingly becoming a competitive advantage for organizations across industries and sectors. Any organization that generates, collects, stores, and uses data can benefit from a data estate. A well-managed data estate also helps organizations to comply with relevant regulations and standards governing data privacy, security, and governance. The industries reaping the benefits of data estates include:

  • Government agencies
    A data estate helps government agencies manage large volumes of data related to citizens, public services, and policy-making and make data-driven decisions more quickly.
  • Large businesses
    A data estate helps businesses manage their data assets, gain insights into customer behavior and market trends, and make data-driven decisions while mitigating risks and complying with regulations.
  • Educational institutions
    A data estate helps educational institutions manage student, research, and administrative data, gain insights into student performance and resource allocation, and optimize their services.
  • Healthcare providers
    A data estate helps healthcare providers manage patient, clinical, and administrative data, gain insights into patient outcomes and resource utilization, and improve patient care and outcomes while complying with regulations.

Data estate success stories

It is no surprise that many of the world’s most well-known and successful companies are also the proprietors of well-designed and highly coordinated data estates. These companies represent just a few examples of data estates leading to enhanced brand value and competitive advantage:

  1. Netflix
    Netflix is a company that has been heavily investing in its data estate for several years. Their data estate helps them to improve their recommendation algorithms and personalize user experiences. Netflix uses a combination of open-source technologies and their own custom-built tools to manage their massive data sets.
  2. Airbnb
    Airbnb is another company that has built a successful data estate. Their data estate helps them to analyze their users' behaviors, preferences, and needs. This information is then used to optimize their platform and make strategic decisions. Airbnb leverages many open-source technologies in their data state but has also invested heavily in proprietary architecture.
  3. Uber
    Uber is a company that relies heavily on its data estate to power its operations. They use data to manage their drivers, optimize their routes, and improve their user experiences. Uber's data estate is also used to analyze the performance of their platform and make strategic decisions. Due to a series of hardware disruptions, Uber recently began migrating portions of their data estate to multiple cloud providers.
  4. Amazon
    Amazon has been building its data estate for decades. The unprecedented success of Amazon, as they emerged from the ruins of the dot-com boom, was directly attributable to the performance of the Amazon data estate. Amazon Web Services (AWS) is now utilized frequently by other companies as they begin to build their own data empires.
“You collect as much data as you can, you immerse yourself in that data but then you make the decision with your heart.”
Jeff Bezos

The future of data estates

The future of data estates is likely to be shaped by several trends and developments. As businesses collect more data and seek to extract more insights from it, data estates are likely to continue growing in size and complexity. Advances in technology, such as the Internet of Things (IoT), will create new sources of data, driving this growth. However, as data estates become larger and more valuable, there will be greater concern about privacy and security. Businesses will need to invest in technologies and practices that protect their data from unauthorized access, theft, and misuse.

AI and data estates

Data estates will increasingly be used to train and power artificial intelligence (AI) systems. AI will be used to automate data processing and analysis, identify patterns and insights, and make predictions and recommendations. Cloud computing is likely to become even more integrated with data estates, as businesses seek to leverage the scalability, flexibility, and cost savings of cloud infrastructure. This integration will enable businesses to store and process larger volumes of data, while also making it easier to share data between different teams and systems.

As data estates become more accessible and user-friendly, there will be a greater focus on democratizing data. This means making data more accessible to non-technical users and enabling them to extract insights and make data-driven decisions. Overall, the future of data estates is likely to be characterized by growth, innovation, and new challenges. Businesses that are able to stay ahead of these trends and invest in their data infrastructure are likely to be well-positioned to succeed in the years ahead.


When considering the analogy between the estate based on land ownership and the data estate, remember the importance of the quality of the land, its potential usefulness, and its accessibility. Careful manicuring never hurt either...

  1. The data estate is a modern concept that helps organizations manage their corporate data systematically, and it encompasses all data sources, tools, and technologies used to collect, store, process, and analyze data.
  2. Data estate success is less dependent on its size and more dependent on advanced tools like cloud integration, artificial intelligence (AI), and machine learning (ML) to gleam insights from the data and apply them more succinctly.
  3. Data estate infrastructure can include data warehouses and data lakes, and they provide complementary storage and management solutions for structured and unstructured data. Data lakes are often used for exploratory analysis and data discovery while data warehouses are used for business intelligence and reporting.
  4. A  well-managed data estate is increasingly becoming a competitive advantage for organizations across industries and sectors, and any organization that generates, collects, stores, and uses data can benefit from a data estate.
  5. The return on investment for recharacterizing data footprints is (we believe) certainly there. The team, vendors, and executive management start to understand and reframe their mind around a data estate, and its intrinsic value to the entire organization over time.

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