DataIQ Member’s Briefing – Can we fix it? The problem with data quality

DataIQ members agreed that quality is a must to become a mature and successful data organisation, but how can data quality issues be addressed?

Data quality was a topic of conversation at the recent DataIQ 100 Summit in Miami, Florida.

Tackling the challenges of data quality

Quality is the bedrock that data-driven decisions are made from, but how does the importance of quality get shown to non-data teams and how much attention is it given?

How to address inevitable data quality issues

Much like death and taxes, issues with data quality are a part of life for data practitioners – but there are steps to be taken to reduce any impact poor quality data may have on a business.

CDO Challenges – Improving data quality and data governance

[…] a data office, the first step is wider data education for the organisation. A CDO needs to ensure that key decision makers understand the difference between data quality and data governance, but also how they work together to achieve business objectives. Starting with the basics, make sure team members understand that data quality […]

How do you influence data owners to be data stewards?

[…] leaders championing the reasons behind why excellence in data stewardship is needed, and a bottom-up approach from everyone that utilises data for their own objectives demonstrating data quality needs and suggesting improvements. Education is a huge part of the challenge, and it was agreed by all participants that, ultimately, everyone is responsible for data, […]

How to persuade data owners to be data stewards

[…] from executives and leaders championing the reasons behind why excellence in data stewardship is needed, and a bottom-up approach from everyone that utilises data for their own objectives demonstrating data quality needs and suggesting improvements. Education is a huge part of the challenge, and it was agreed by all participants that, ultimately, everyone is responsible for data, but this […]

Improving BI data quality

Data quality in business intelligence is not often recognised as an issue in itself, yet its impact on the reliability of reports and KPIs can be significant. This guidance note offers an approach for improving your CARBON score for BI by one or two points.

Demonstrating ROI on Data

[…] Experian QAS even put a headline-grabbing figure on this – £8 billion. That is what it estimates UK businesses could generate in incremental profit from improving the quality of customer and prospect data. The figure is an extrapolation from the average profits which companies in the survey calculated to have generated as a result […]

DataIQ members discuss threat and the difficulties surrounding it.

Key data leader challenges in 2024: Part three – Threat

[…] futuristic boom in technological capability, there is a lot of new territory the data office must approach with suitable armament. First, there is the threat that poor quality data imposes on internal decisions and operations, identified by a decent portion of data leaders. Next, keeping compliance tight and the data under impenetrable lock and […]

Camden Council and the benefits of opening data

Sudip Trivedi is the head of data and analytics, and connectivity business partner at Camden Council. Central to his role is improving the quality of data within the borough and allowing more people to access that data. Trivedi came to the ...

Blend provides insight into seven essential aspects of successful AI scaling.

The Critical 7: Scaling to production level AI

[…] and feed AI models is accurate, consistent, secure, and compliant with relevant regulations. Without proper data governance, AI initiatives can face numerous challenges, such as: Poor data quality leading to inaccurate predictions and flawed decision-making. Inconsistent data across different systems hindering the integration of AI models into existing workflows. Inadequate data security measures, exposing […]

Should businesses decentralise data to keep evolving?

[…] contemporary technological developments and easier access to training, the system can easily become clogged or face multiple bottlenecks. DataIQ members frequently highlight speed of data access and quality of data as their key bottlenecks and this framework, while effective at securing high quality data, can often be a slow process. Looking up On the […]

DataIQ members discussing their AI adoption journeys at a roundtable hosted by Alteryx.

AI adoption in a world of data quality and data governance concerns

Different leaders delved into how there is a varying level of importance between data culture and data quality and collaborated on how AI adoption can be effectively achieved. There have been numerous conversations around how data culture can be built, examining data quality, and defining data culture, but the specifics of weighing up the […]

Ensuring high quality data processes in insurance

[…] and of being a data-centric organisation.” Therefore, strong data architecture had to be part of the solution, as did portfolio management, devops and a focus on data quality. Fernqvist said that they had to architect systems at the outset from a data standpoint to drive value from the data in them, in addition to […]

How to overcome data challenges with AI adoption

[…] a dynamic landscape for CDOs,” said Hunt. “There is now heightened pressure to ensure data readiness for AI adoption, as highlighted by the need to maintain data quality, address privacy risks, and promote transparency in AI models. Furthermore, the deployment of generative AI tools has brought both opportunities and challenges, requiring data leaders to […]

Integration and data talent change to achieve long-term success

[…] group offerings. With £270 billion of assets under administration, Phoenix Group supports 12 million customers with their pensions, savings and life insurance products to provide the highest quality levels of retirement possible. Due to the nature of Phoenix’s business, there is heavy regulation, meaning compliance is of utmost importance as the security of customer […]

“It’s not always the weather” – Optimising KPI development and delivery

[…] However, a critical step in maturity is to migrate the following away from LOBs and into BI or D&A teams: data governance – ensuring data lineage and quality, as well as acting as gatekeeper; standards and standardisation – working with LOBs to define KPIs to common standards. Data governance and standards for key performance […]

Bloomberg’s best practice for data annotation

[…] learning researchers do not possess expertise in annotation best practices. But those who do – or those who develop it – can achieve recognition for providing high quality annotated data for other researchers. DIQ: How important is domain expertise in the data subject area, ie, do stakeholders/SMEs need to be involved to contribute to […]

Build and future-proof your skills with DataIQ Leaders

[…] and insights. Table 1 – Top 10 skills in 2015 1 Complex problem solving 2 Co-ordinating with others 3 People management 4 Critical thinking 5 Negotiation 6 Quality control 7 Service orientation 8 Judgement and decision making 9 Active listening 10 Creativity DataIQ Leaders programme of skills development Our programme has been built […]

Join the dots: Why tackling data issues is key to digital transformation

This report, a collaboration between DataIQ and Experian, is a deep dive into the how and why of digital transformation as well as the role data quality and data management play in its success. Download this report to understand the importance of data quality and data management and how to prevent data quality pitfalls […]

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