Struggling to scale analytics and AI? Data quality may be the culprit

Around 90% of business leaders express difficulty scaling data analytics and AI across their enterprises. And usually, it comes down to data quality.

If your organization is struggling to scale analytics and AI, you’re not alone. We’ve come to the aid of many clients challenged with realizing their investments in advanced data analytics and AI. According to a 2020 Forrester survey, 90% of firms have difficulty scaling data analytics and AI across their enterprises. And data quality is the top culprit, followed closely by data integrations and data access. In fact, the report goes on to note that:

58% lack confidence in the quality of their data sources
54% lack integration with analytics, data science, and AI platforms
53% lack data access and democratization
40% have low confidence in data governance issues
37% lack confidence in connecting data sources

Without properly curated data, AI and analytics initiatives fall short, leading to increased costs, missed deadlines, and regulatory risks. But to compete and thrive in this new digital age, corporations must leave legacy technology behind and embrace automation, predictive analytics, and the myriad benefits that advanced data analytics and AI offer.

The solution? Look to external experts like EveryIT, with proven skills, expertise, and experience in helping enterprises overcome data obstacles.

A best-practice approach

When we partner with clients struggling with data-centric issues, we work to understand your business first and then deliver the right technology services to propel your business forward. Every engagement begins with an effort to understand your organization’s pain points and business needs. We construct a data and analytics roadmap and plan out a data strategy and data ecosystem. We then implement a data architecture and integrate data foundations and platforms, structuring data through data labeling, platforms and engineering, and data recognition.

Once your data structure is established, and you’ve got quality, integrated data, we set up everything you need to derive actionable insights, including business intelligence and visualizations through intelligent dashboards, data analytics, and self-serve reporting. At this point, you’re ready to innovate solutions, leveraging data science and automation through AI and machine learning.

Every EveryIT engagement is built on three essential best practices:

Data governance (data quality): The process, roles, policies, and standards to ensure your data is high quality, meaningful, available, usable, timely, accurate, and secure.
Data fabric/data mesh (data integrations): Technical architectures that facilitate the end-to-end integration of your various data pipelines, data stores, and cloud environments through intelligent and automated systems.
Data democratization (data access): Making digital information accessible for your people, processes, and technical platforms, building the foundation for self-serve analytics, predictive analytics, and data-driven decisions across the data ecosystem.

These best practices help ensure data quality and consistency across your organization, instilling confidence and producing better, more actionable insights to inform better business decisions. They also help to establish transparent policies and platforms to support enterprise-wide data infrastructure, allowing your organization to be more agile. Finally, these best practices enable seamless growth and scalability, regardless of the exponential increase in data volume.

The EveryIT engagement model

As a global technology provider with more than 26,000 experts across five continents, EveryIT has become the partner of choice for Fortune 10-2000 companies for more than 27 years. We offer onshore, offshore, and nearshore delivery.

We tailor our engagement model to suit your unique technical environment, project oversight models, product ownership matrix, and distributed / remote team structure. With these engagement models, you can: