Leveraging Analytics and Machine Learning for Data Quality Excellence​

For large companies and major corporations, data is an immensely valuable asset when properly harnessed. It’s no wonder the global big data analytics market is forecasted to grow to $103 billion US dollars by 2027.

High-quality, trustworthy data fuels game-changing benefits like optimised business intelligence, automated decision-making, personalised customer experiences, and innovative AI and machine learning capabilities. 

Before that potential can be realised, data preparation tools and methodologies must come into play to establish a foundation of accurate, reliable data. Achieving and maintaining reliable and consistent data quality at an enterprise scale can be an uphill battle. With data flooding in from a myriad of sources, fragmentation and quality issues like duplication, inconsistent data governance, and a lack of metadata proliferate.

This “mess” of data becomes exponentially harder to deal with via traditional data preparation processes, especially when factoring in unstructured data formats which account for 90 per cent of the typical organisation’s data landscape.

Analytics + AI: The Data Quality Edge

To truly harness the power of these vast data assets at scale, organisations need to move beyond traditional data preparation software and processes. Intelligent information management platforms with inbuilt analytics and AI technologies offer a new generation of intelligent capabilities to automate data quality processes with speed and accuracy.

Here are key areas where analytics and AI can optimise data quality:

Automated Data Discovery and Classification

Using natural language processing and other AI techniques, organisations can automatically discover and classify information from multi-format data sources including unstructured “dark data” previously invisible. AI-enabled discovery tools provide a way to illuminate hidden data assets, an important step in the data preparation process.

The benefits of AI technologies in this space also include the ability to use your own taxonomy without having to train the system when it changes. More so, AI technologies help you improve your taxonomy by making intelligent suggestions for improvement based on the data it discovers as your business evolves. This ensures businesses always have the right frameworks in place to meet their changing needs – a must for effective data preparation for machine learning.

Data Cleansing and Transformation

Machine learning models can comb through data repositories to identify anomalies, remove redundancies, fill in missing information, normalise taxonomies, and structure data in a more organised manner.

Machine learning models can also be more closely supervised, trained and improved, so they can better adapt to your environment and needs. These data preparation best practices set the stage for AI and ML to flourish at scale.

Adaptive Data Quality Monitoring

Analytics provide comprehensive monitoring of data pipelines, data provenance, and quality metrics. AI models can detect drift, deviations or patterns of errors in data streams and trigger resolution actions automatically. This maintains reliable data quality over time and reduces the manual overhead traditionally associated with data preparation tools.

Intelligent Data Cataloguing

With machine learning models powering cataloguing, organisations can implement intelligent, dynamic metadata management. Smart data catalogues can ensure metadata consistency, maintaining accurate data assets and aligns with best data preparation software solutions.

By injecting analytics and AI across the entire information management lifecycle, organisations can establish continuous, automated cycles of data quality improvement and generate the highest quality data ready to supercharge a myriad of business initiatives.

The EncompaaS Advantage

Of course, the insights derived from advanced analytics are only as accurate and actionable as the underlying data quality that feeds those models. That’s why EncompaaS has developed a platform designed to tackle the challenges of data preparation for AI while supporting high data quality.

The EncompaaS intelligent information management platform uses next-generation AI technologies to find, enrich, organise and de-risk structured, unstructured and semi-structured content anywhere in the enterprise, enabling organisations to:

• Identify and extract data – Automatically identifying, classifying and extracting information from all data sources, including unstructured formats previously ignored
• Enrich metadata – Enriching data through the automatic application of metadata to make content more usable, manageable and accessible to permissioned users
• Classify information intelligently – Classifying discovered data using your taxonomy, relevant perspectives and growing areas of interest or concern
• Optimise taxonomies – Continuously suggesting improvements to the taxonomy, based on the evolving nature of the content created by your organisation, in a supervised yet seamless manner
• Normalise data – Cleaning up data by removing duplicate or redundant records, and by creating a foundation of normalised data
• Monitor data quality in real time – Continuously monitoring data by leveraging advanced analytics in easy to digest dashboards, providing insights into your entire data landscape.

With an increasing volume and complexity of data within the enterprise, organisations can no longer rely solely on manual data preparation processes to meet increasing organisational demands.

To truly leverage and capture the value of enterprise data, organisations must look to analytics and machine learning, within intelligent information management platforms, to enhance business outcomes.

EncompaaS combines the best data preparation software with AI and machine learning to ensure scalable, compliant, and high-quality outcomes.

By extending governance, automation and AI capabilities across legacy systems and modern platforms, EncompaaS provides a configurable framework that aligns with your organisation’s needs.

To learn more about how EncompaaS can help your organisation achieve data quality excellence through AI, contact us or book a demo.