In data mining, data can be both an advantage and a burden
In 2016, Dell Technologies commissioned our first Digital Transformation Index (DT Index) study to assess the digital maturity of businesses around the world. Since then we have commissioned the study every two years to track the digital maturity of businesses.
Our third installment of DT Index, launched in 2020 (the year of the pandemic), revealed that “data overload / unable to get insights from the data” was the third highest barrier to change, from 11th place in 2016. That’s a huge leap from the bottom to break the high ranking of barriers to digital transformation.
These insights focus on the future. intelligence-data has the potential to be the number one barrier to business transformation while also which is their greatest asset. To find out part of why this shift is happening and where businesses need more help, we commissioned a study with Forrester Consulting to delve in-depth.
The outcome study, in line with a survey of 4,036 senior judges with responsibility for their companies ’data strategy, was titled: Unveiling Data Challenges Affecting Businesses Around the World, available to read now.
In fact, the study confirms our concerns: in this decade of data, data has become a burden and an advantage for many businesses-where one depends on how readily the business data is.
While Forrester identifies many data contradictions that hinder businesses today, three main contradictions stand out for me.
1. The rational contradiction
Two -thirds of respondents say their business is driven by data and declare that “data is the blood of their organization.” But only 21% say they treat data as capital and prioritize its use across business today.
Obviously, there is a disconnect here. To provide clarity, Forrester created an objective measure of the data readiness of businesses (see figure).
The results show that 88% of businesses have not yet developed either their data technology and processes and / or their data culture and expertise. In fact, only 12% of businesses are defined as Data Champions: companies that are actively engaged in the same areas (technology / process and culture / skills).
2. The “want more than they can afford” opposite
Research has also shown that businesses need more data, but they have a lot of data to keep in mind now: 70% say they gather data faster than they can analyze and use, even though 67% say as they always need more data than they currently provide capabilities.
Even if this is an exception, it’s not all that surprising when you consider the research as a whole, as the proportion of companies that have not yet secured data advocacy at the Boardroom level and are back to an IT strategy that not measurable (i.e., bolting on additional data pools).
The implications of this contradiction are deep and very broad. Six in 10 businesses are struggling with data loopholes; 64% of respondents complained that they had so much data that they could not meet security and compliance requirements, and 61% said their teams were already covered by the data they had.
3. The “seeing not doing” negation
As economies suffered during the pandemic, the sector in demand expanded rapidly, igniting a new wave that preceded data, data wherever businesses paid for what they used and only used. they need – determined by the data they generate and analyze.
Even if these businesses are thriving, and very good, they are still small in number. Only 20% of businesses are moving most of their application and infrastructure to a single-service model — even if more than 6 in 10 believe a single-service model can make companies more proactive, size, and provision application without complexity.
Simultaneously achieve good results
The research is exciting, but there is hope ahead. Businesses seek to transform their data strategies into a multi-cloud environment, by moving to a data-as-a-service model and automating data processes with machine intelligence.
Granted, they have a lot to do to make good bombs for a lot of data. However, there is a way forward, by first modernizing their IT infrastructure so that they can meet the data where it resides, on the edge. This includes bringing businesses ’infrastructures and applications closer to where data needs to be retrieved, analyzed and processed-while avoiding data clutter, by maintaining a dynamic multi-cloud operating model.
Second, through optimization data pipes, so data can flow freely and securely as AI / ML is added; and third, by creating software to deliver the self, unified experiences that customers desire.
The staggering quantity, diversity and speed of data may appear to be even more powerful but with the right technology, process and culture, businesses can be distracted by violent data, change with it, and be able to innovate. the amount.
To find out about the study, visit www.delltechnologies.com/dataparadox.
Its content is made by Dell Technologies. It was not written by the editorial staff of the MIT Technology Review.