Businesses suffer from a bad case of TMI
Posted March 07, 2022
Written by Terry May, Xpanxion Technical Writer
It's become the data paradox of our time
In this digital age, when data is at the heart of digital transformation and expected to drive most every business decision imaginable, the proliferation of data and the number of data sources is surging at a staggering rate and becoming tougher to manage.
A study by Forrester asserts this and reveals three particularly telling data paradoxes hindering the path toward digital transformation today.
- 67% of organizations desire more data than they can currently manage, while 70% claim to gather data faster than they can analyze or use it.
The result: While businesses covet more data, they’re overwhelmed with the data they have, and they're wrestling with how to make it valuable.
- More than 6 in 10 businesses think an as-a-service model would help them be more agile, scalable, and release applications without issues. Yet, only 20% of companies have shifted most of their applications and infrastructure to a modern cloud, edge, and other distributed as-a-service models.
The result: Even though businesses see tremendous value in modern architectures, the vast majority of companies have not made a complete migration. They’re holding on to difficult-to-use legacy systems, time-consuming manual processes, and hard-to-access data sources.
- Two-thirds of respondents claim to be “data-driven” organizations and view data as “the lifeblood of their organization.” But, only 21% treat data as capital and give it a companywide priority.
The result: Businesses drastically overestimate their data readiness (Forrester responded by creating a Data Readiness Scorecard).
Hurdling the data overload roadblocks
No matter how you dice the numbers, they translate to most businesses' inability to realize time to value. Whether the roadblocks are accessing the data, transforming it into analytical formats, analyzing it, or getting it to the right place at the right time, organizations are constantly wrestling with how to decrease the time it takes to turn their data into value.
These are ironic problems to have in this decade of data, to say the least. The ramifications of data overload are extensive and profound. Without extracting value from data, businesses have no clear path to digital transformation. Consequently, they have no way to achieve data sovereignty.
Forrester points to three main obstacles that contribute to data overload:
- Inadequate in-house data scientists and technical talents
- Business and data silos (6 in 10 businesses contend with silos that render the data hard to access)
- Sluggish and arduous manual processes
In other words, for businesses to effectively tap value from data and achieve data excellence, they must make these moves with the right technologies, culture, and teams:
- Invest in a data-ready skillset and culture. A precise set of skills is required to glean insights from data. Organizations should not cut corners here. They need to discover and invest in the right data-ready talent and culture, whether in-house, through partners, or other third parties. Teams should be cross-functional and highly collaborative to achieve agility and adapt to rapid change.
They need to cultivate talent beyond training and certifications in data literacy by inciting employees and teams to innovate in data and data analytics, and they need to be constantly evangelizing the democratization of data.
- Bridge the gaps between data, applications, and infrastructures. By bringing the infrastructure and its applications closer to the data, decision-making can occur at the right time, in near real-time, and when the data is at its freshest state. This move entails the adoption of modern IT infrastructures and multi-cloud environments so business processes and applications can run closer to where the data resides, is collected, analyzed, and acted upon (at the edge).
- Move to a data-as-a-service (DaaS) model. As the name implies, DaaS is a software service for data. It encompasses data management, storage, and analytics, and it allows data to be shared across clouds, systems, gateways, applications, etc., regardless of the data source location. Common APIs are used to access the data. DaaS is how businesses can quickly and efficiently break through the data silos to create new value.
- Automate across the lifecycle. The sheer velocity, abundance, and diversity of today’s data requires businesses to take advanced automation seriously by leveraging machine learning (ML) and AI to automate business and data processes, pipelines, and QA testing so the data can flow effortlessly across its lifecycle.
Today, company success is increasingly measured by how well an organization can exploit data, apply analytics, and embrace new technologies, processes, and cultures. And although the value of most of today’s data remains untapped, there is a path toward data excellence...and it's paved with the right blend of data-ready technologies, cultures, and teams.
To learn how Xpanxion can help your business become data ready, tap data’s full potential, and draw business insights needed for today’s data economy, click here to speak to our data experts.
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