High-quality data is the foundation for success in today's data-driven world. Across a wide range of applications, from machine learning and data analysis to business intelligence and dashboards, poor quality data can be a significant obstacle to achieving your goals. 7xData are dedicated to helping organizations overcome the obstacles posed by poor quality data.
In today's data-driven world, structured data is the holy grail for businesses. But the reality is, much of the information that holds valuable insights exists in semi-structured or unstructured formats, or worse legacy systems with little to no documentation. Metadata is the key that enables semi-structured data to be better catalogued, searched, and leveraged for powerful machine learning applications.
Gain a comprehensive 360-degree view of your data that empowers you to make more informed, data-driven decisions. 7xData helps clients implement robust data governance processes and policies. This includes defining data ownership, establishing data quality standards, and implementing data cataloguing systems to improve transparency and accountability.
Using our software partners data quality and profiling tools, 7xData can help you identify and rationalise reference your data sets and standardise common fields. 7xData’s profiling expertise can help you ensure your data is accurate, complete, and properly formatted, allowing you to draw reliable insights without inaccuracy, bias, or hallucination and make informed, data-driven decisions to propel your business.
Are you tired of the headaches and costs associated with poor data quality? Disparate data sets, duplicate processes, and inconsistent standards can cripple your organization's ability to make informed decisions and drive growth. Our experienced team of data experts and world-class tools can help you pinpoint the root causes of your data quality problems and implement sustainable solutions.
Inconsistent data standards and business rules across your organization create unnecessary complexity and friction, that increase costs and reduce efficiency. Our experienced team of data experts and world-class tools can help your data transformation initiatives deliver tangible value, to improve decision-making, operational efficiency, or new revenue opportunities.
Whether your goal is to improve decision-making, boost operational efficiency, or uncover new revenue opportunities, 7xData has the expertise to get you there. We'll partner with you every step of the way to ensure your data transformation delivers tangible business value. Don't let poor data quality hold your organization back any longer.
Our 7xMethodology encompasses a rigorous Data Quality assessment that helps us identify potential risks and disruptions your business may face due to poor data quality. By evaluating the seven risks of data quality, we can pinpoint areas of concern and develop strategies to mitigate the impact of low-quality data on your operations.
Data quality is a critical aspect of any business operation, and adhering to the 7 principles of data quality can ensure the integrity and reliability of your data. The first principle is accuracy, which demands that data be free from errors and correctly represent the real-world entities it describes. Completeness, the second principle, necessitates that all relevant data is captured and available for use. Consistency, the third principle, requires data to be uniform and coherent across systems and sources. Timeliness, the fourth principle, dictates that data must be up-to-date and available when needed. The fifth principle, conformity, ensures that data conforms to defined rules and constraints. Uniqueness, the sixth principle, mandates that each data instance is distinct and can be uniquely identified. Finally, integrity, the seventh principle, involves maintaining the relationships and dependencies between data elements to preserve their context and meaning.
NHS Digital required support with the implementation of a big data program and GP Practice patient experience project. The project had been start-stop for a number of years due to technological and political constraints. Progress had been made in this area and a solution was required to deliver the big data programme to various customers.
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