Articles about data governance

Data comes in many forms, it may be structured, it may be unstructured, it could be sensitive or purely statistical. Whatever it looks like you can only benefit from it if you know what you have, where it can be found and how to access it.

We spoke to Brett Hurt, CEO and co-founder of data.world to discuss how enterprises can understand their data and derive the maximum value from it.

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As more organizations look to deploy AI and LLMs across their operations to drive a competitive edge, ensuring the data being used to power these innovations is of high enough quality is becoming business critical. To give these AI and LLM innovations the best chance of success, many organizations are turning to hybrid cloud infrastructures, making use of both on-premises and cloud to ensure they can tap into valuable data.

But hybrid cloud infrastructure comes with its own set of challenges, particularly when it comes to data governance. Inherently, a hybrid infrastructure allows data to move between environments, which can make that data vulnerable to not only security risks but also growing regulatory compliance considerations. With so many regulations surrounding data firmly in place, such as the EU’s GDPR and the US HIPAA, compliance is crucial to business operations. GDPR fines alone can reach 2 percent of global turnover. A penalty of this magnitude would have a huge impact on the entire organization.

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Improving data quality (42 percent), security (40 percent), and analytics (40 percent) remain top data governance drivers, but in 2024 ensuring data readiness and quality for AI (34 percent) has made the list as the fourth most cited driver of data governance programs.

A report from Quest Software and ESG (Enterprise Strategy Group) also shows organizations report evolving data and governance to an AI-ready state (33 percent) as a top three bottleneck impacting the data value chain, behind understanding the quality of source data (38 percent) and tied with finding, identifying and harvesting data assets (33 percent).

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The term 'prompt engineer' has become a bit of a buzz word for future-of-work topics. What isn't discussed as much, and is arguably more important to AI models, is the role of the data governance architect.

Satish Jayanthi, CTO & co-founder of Coalesce believes that without good data governance, organizations will go nowhere in extracting value from AI and ML models. We talked to him to find out more.

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Although chief information officers have been at the forefront of enterprise digital transformation efforts for years, they are still too often reduced to the company’s "technology expert." Even if the reality is different, perception counts for a lot. It’s now time for CIOs to change that perception and evolve into more wide-ranging business strategists, enabling their IT departments to leverage their expertise for high-value business outcomes.

The good news is that most enterprise CIOs already have nimble, intelligent and scalable technology to facilitate that change. What’s needed is an approach that improves efficiency and increases productivity in ways that are directly tied to company goals. Here are four questions every CIO of a B2B enterprise should be asking as they seek to maintain the momentum of their digital transformation.

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Achieving business success and making informed decisions requires high-quality data that organizations can trust. However, achieving data quality can be complex and time-consuming, forcing data and analytics leaders to choose between supporting business outcomes and ensuring compliance with data privacy and regulatory needs. Here’s how organizations can achieve business outcomes and compliance with regulations and privacy policies.

Data is often referred to as the new oil for a good reason. In today’s digital age, we are generating and collecting data at an unprecedented pace. As Sir Tim Berners-Lee said, "This precious resource will last longer than the systems themselves." IDC projects that by 2025, we will hit 175 Zettabytes of data. However, the challenge for businesses is how to turn this raw data into valuable insights. This is where data quality and governance come in.

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These days no important topic is worthy of the name if it doesn't have a day devoted to it. Today (January 28) it's the turn of data privacy -- or data protection depending on who you talk to -- to take its turn in the spotlight.

As organizations gather ever more data, concerns around how it is stored and used have grown which has led to legislators taking an interest too.

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No longer the new 'big thing', the cloud has matured into something that almost all organizations rely on daily. But it's still evolving and its importance has grown over the last two years as we've switched to remote and hybrid working.

Here are some expert views on what lies ahead for the cloud in 2023.

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Since the explosion of technology in the last few decades, data has been increasingly positioned as a silver bullet that can fix all the trials and tribulations of the modern world. For those giant tech companies who amassed mass amounts of (mostly) third-party data, data was the new oil -- sold in barrels to any company wanting to find and scale an audience. But KPIs on data effectiveness became increasingly viable, businesses began to question the amount of data they’d bought.  

Parallel to this, governments and consumer rights groups became aware of the increasing volume of unwanted noise being thrown at potential clients and customers. Businesses, both B2B and B2C, became liable for data missteps -- case in point with Meta being fined 17m euro for what amounted to bad data housekeeping.

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Data is increasingly one of the most valuable resources that businesses have, but extracting that value requires effective management of content.

A new survey from Rocket Software of more than 500 corporate IT professionals across multiple industries in the US, UK and APAC regions shows that business data is still vastly unstructured with 81 percent of respondents indicating that at least some of their data is considered 'dark'.

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Almost any information not located inside the DBMS is classified as unstructured data. Today, unstructured data is one of the main information assets of any company. It includes electronic documents and files located in corporate storage units, namely office documents, PDF files, scanned copies, and audio and video content.

The problem of protecting unstructured data storage units is acute in many companies. Before proceeding to the protection methods, it is necessary to determine why the task of protecting such systems is vital.

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In a new survey 42 percent of respondents say at least half of their data is 'dark data' -- retained by the organization, but never used.

The study from Quest Software, in collaboration with the Enterprise Strategy Group (ESG), highlights the top challenges and innovations in data governance, data management and DataOps.

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The widespread shift to working from home in 2020 forced many companies to rapidly adopt cloud technologies to enable remote workforces and customer connections. However, some important IT planning may have been overlooked amid the urgency to transition to the cloud. A long-term plan around data governance -- the approach to managing and using data securely in enterprise systems -- may not have been implemented when moving to the cloud.

Understandably, data governance may not have been a top priority for companies in the pandemic’s early days. But now, as companies review their cloud strategies and contemplate the next steps for maximizing value from the cloud, data governance plays a critical role in cloud optimization. This is especially true as the pace of data creation has rapidly accelerated since 2020. If not kept in check, the rapid creation of data can result in data sprawl, a staggering amount of unorganized data that leaves your IT environment in disarray.

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Bad data can lead to disasters that cost hundreds of millions of dollars or -- believe it or not -- even the loss of a spacecraft.

Without processes that guard the integrity of your data every step of the way, your organization might suffer catastrophic mistakes that erode trust and lose a fortune. As a reminder to make sure that high-quality data is an end-to-end priority for all types of industries, let’s look at some of the biggest data quality incidents in recent pop culture history.

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The three slices of the data pie -- data governance, data privacy and data security -- are often lumped together -- but although they naturally overlap, there are crucial differences that are important to understand.

Let’s slice up the pie. First, there’s data governance. You can think of it as the cornerstone; the thing that holds everything together. If you have the right data governance in place for all your data assets then it's much easier to apply the right privacy and security controls.

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