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When it comes to data, one fact has endured from the origin of mankind: it is inextricably linked to the decision-making process. The more data that we can include in our analysis, the more we can understand the past and navigate the future effectively.

Practices in the capture and storage of business data often from diverse global sources must evolve in response to the skyrocketing quantity of data that businesses produce and their need to act on it faster than ever. One research firm, Statista, forecasts that there will be 181 zettabytes of data by 2025, up from 97 zettabytes this year. A zettabyte is one billion terabytes. The chart below depicts this growth trajectory.

Companies can only store, manage, and act on data at the required speed by modernizing their data infrastructure. To do so, they need to move past the legacy construct of monolithic systems, which store a single type of data in siloed fashion with no movement of data between them. By modernizing such systems in the cloud, companies enable unification of data with robust new functionality and services that dont exist in legacy systems.

To understand the value of modernizing data in the cloud, its helpful to start with this baseline, data-oriented definition of the cloud, a vast network of remote servers hooked together and meant to operate as a single ecosystem. These servers store and manage data, run applications, or deliver content or a service such as streaming videos, web mail, office productivity software, or social media. Users can access files and data from any Internet-capable device making information available anywhere, anytime.

Because of complexity, silos, and the need to have vast amounts and sources of data accessible at high velocity, the need to modernize data infrastructure takes on more urgency every day. Moving data to the cloud is the most compelling option because the cloud will deliver (at least) three critical benefits:

The cloud allows any organization to ingest, analyze and contextualize data at high speed. And we all know that fast decision-making and real-time actions are key to capitalizing on business opportunities in the Acceleration Economy.

In addition, the cloud requires low to no maintenance on the part of the customer, improving security and protection of data and systems, as well as data recovery in case of any threat or incident. This is especially important for highly regulated industries that require large volumes of historical data and regulated compliance by implementing business rules that apply to many systems and tools at once.

There is not a magic recipe for any organization to transition from traditional or monolithic data systems to a cloud data system. That entails moving from a physical infrastructure that has been designed as a reflection of a traditional, hierarchical organization towards something that is more flat, horizontal, and collaborative with fewer boundaries and barriers.

However, there are some cloud data modernization recommendations that should hold true in virtually all industries and use cases:

While the points above are ordered based on a logical sequence, the first point, relating to people, must be addressed at the outset. First, moving to the cloud challenges the status quo (data ownership, silos, org structure) of many organizations. With cloud technology, we are moving from a practice of data to report to decision to a more streamlined practice of data to decision; the implications of this new paradigm can be highly impactful.

Join us on October 27, 2022 for Acceleration Economys Data Modernization Digital Battleground, a digital event in which four leading cloud vendors answer questions on key considerations for updating data strategies and technology. Register for free here.

So, when embarking upon modernization of the data stack, a company should start by educating (or re-educating) the entire workforce, starting from the top of the hierarchy, about being open and transparent, practicing collaboration among teams (which team generates and analyzes specific types of data), delegating more decisions to others, and learning about new technologies and tools. Once the cultural element has been addressed, let engineers and technical people handle the technical aspects of cloud data modernization.

Once migration and modernization have happened, the tech team must stay in close contact with the cloud infrastructure vendor(s) and have a clear understanding about the responsibilities of each party. It is very important to actively monitor cloud performance, storage, and applications usage as well as vendor billing practices known as FinOps. Close internal monitoring of billing, combined with good communication with the provider(s), facilitates solid operational results and keeps the cloud provider(s) fully engaged on your behalf.

There are numerous vendors offering cloud solutions, but again, each and every organization is unique, with a different vision, strategy, and goals. It is easy to understand, therefore, why each vendor is more suitable for certain use cases, industries, and businesses, so a deep understanding of each vendors product offering is critical before adopting one solution over others.

An evaluation of vendor strengths and alignment with your business goals and culture must include:

In the analysis above, Ive focused on the why and how of data modernization in the cloud and shared important technical considerations.

Theres one more critical technology factor to consider, and thats the vendor or partner you select to execute on your data modernization goals. In the table below, Im presenting the companies from my direct, hands-on experience and ongoing engagement that are the best candidates to help you, and some key strengths they offer. These companies, of course, are the subject of ongoing analysis at the Acceleration Economy site.

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Why Cloud Data Modernization Is Needed, and How to Make It Work - Acceleration Economy