The Cloud’s Biggest Flaw: Why We Need to Go Beyond a Glorified Workbook


As transformation initiatives continue to accelerate, the cloud remains an essential tool for organizations transitioning from crisis mode to new, more permanent hybrid work practices as well as recession-fighting strategies. As a result, the cloud remains a major focus of investment: Gartner predicts that by 2026 public cloud spending will exceed 45% of all enterprise IT spending – up from less than 17% in 2021.

Massive cloud adoption combined with mass digitization has also impacted the volume of data generated. Today, every business is digital-first, generating terabytes of data every day. Whether it’s the websites and applications that customers use when they buy goods and services, connected objects and other sensors that allow the monitoring of an entire chain in different sectors (such as agriculture, manufacturing or the supply chain): big data now lives in the cloud.

From cloud-based data warehouses to data lakes, companies are turning to the cloud to manage and store massive amounts of data. However, if many companies have a large volume of data, many more are unable to make use of it. With most business process datasets now scattered across different data lakes, data warehouses, and data silos that cannot communicate with each other, profiling, preparing, and building a data pipeline that generates insights has become a common challenge for many organizations.

Despite more than a decade of hype and attention, the cloud has yet to reach its full potential for transforming businesses. The “cloud” can have several different meanings in different organizations. For some, the implementation of the cloud allows companies to have additional data centers geographically close to where their users and/or data are located. This can save time by reducing the number of data moves, while ensuring the necessary legal compliance depending on the use case. For others, “cloud” means taking full advantage of the ever-decreasing cost of data storage compared to on-premises storage. Unfortunately, many companies still focus primarily on the second approach, and cloud adoption strategies remain centered – and siloed – around data storage.

Today, the cost of storage is incredibly low and continues to decline, making the value proposition of creating and storing data an easy equation. However, one of the ultimate benefits of the cloud can quickly turn into a problem.

With the exponential growth of data, companies are already faced with an overwhelming amount of fragmented raw data. Unable to unlock them to find new opportunities for growth and value creation, many are content to hoard them with no end goal or goal.

Moving from data storage to information generation

The importance of data, which is one of the main drivers of business success, cannot be overemphasized. However, clean, structured and standardized data is necessary to provide reliable and accurate information. As the volatile business environment of the past two years has underscored, fast and accurate data-driven decision making is the difference between a successful business and a failing business.

Organizations and business leaders need to have the right information needed to quickly formulate action plans. According to a recent Alteryx study, 62% of practitioners and 75% of middle and senior managers are now expected to make agile and scalable data-driven decisions as part of their daily work. The goal of any cloud computing strategy should always be to facilitate the end result of the business. Rather than just storing data, cloud computing strategies should focus on making the best use of the greatest hardware elasticity available to scale computing resources up or down as needed.

The cloud combines near-infinite storage with the elastic computing capacity needed to rapidly process, analyze, and automate processes, delivering a complete modern data and analytics ecosystem. Harnessing this scalable computing power efficiently is key to leveraging the big data already present in cloud repositories. Integrating advanced analytics into the cloud computing strategy enables the business to move from being “data drowned and information hungry” to analyzing data from different platforms that would otherwise remain siled. and to draw information from these extremely valuable resources.

Fast and scalable data analytics capabilities within reach of any business

Given the amount of data already in the cloud, it is much more efficient – in terms of time and money – to move analysis processes to the cloud rather than moving terabytes of data to a single computer to treat them. However, only a fraction of today’s enterprise data is accessible and analyzed due to its dispersion in different clouds and silos. Cloud analytics (meaning the assessment of data where it resides) is essential for analyzing and unlocking the value of the vast volumes of data held by enterprises.

The greatest potential impact of cloud analytics comes from the combination of data democratization with huge computing resources and data processing and analytical power, which enables large-scale decision-making based on on the data. However, cloud-based analytics also offer tremendous leverage in the form of democratizing data analytics responsibility – helping every employee get the insights they need from massive amounts of data, so more people in the business can consume and analyze it to more easily identify critical patterns and trends.

Today’s ever-changing business landscape demands fast-paced, evidence-based insights and accurate decisions for organizations to thrive. This high demand for data insights puts increased pressure on data and business analysts to produce accurate analytics in a timely manner.

From data accessibility to data literacy: The need to democratize data analytics

When business leaders think about analytics, they should view it as a collaborative process across the entire organization. Ensuring everyone – from IT, to subject matter experts and business analysts, to engineers and data scientists – can collaborate, develop models, solve problems and generate insights is essential. from the data. If data is the fuel needed to understand the business, a skilled data analytics workforce is the engine that powers this process, delivering new insights and innovations previously out of reach.

However, today there simply aren’t enough people with data science skills to meet the data analytics needs that businesses need, and many employees are still mired in unproductive work using old and inefficient spreadsheets.

Since only a fraction of the data within the enterprise is accessed and analyzed, unlocking value from the huge volumes of data held by organizations requires a dramatically expanded strategy to overcome the stagnant use of the cloud as a filing cabinet. glorified and fiercely guarded – a strategy that focuses on human intelligence and analysis for all. The cloud makes data and analytics more accessible. By delivering speed of execution and ease of use through enterprise-wide access to self-service, browser-based analytics, business leaders can also help the next generation of data workers put data-driven insights at the heart of decision-making.

As the pace of change continues to accelerate, only organizations that empower people with data literacy while providing faster, more accessible cloud analytics will be able to deliver business insights at scale.





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