Five Common Pitfalls on the Path to Becoming a Data-Driven Enterprise

Five Common Pitfalls on the Path to Becoming a Data-Driven Enterprise

Your company collects data from different sources and then you analyze the data to help make the right decisions. But you aren’t quite getting the results that you expect. Maybe the insights aren’t accurate. Perhaps the process is time consuming and cumbersome. Or you are only currently using data for a few use cases and struggle to implement organization wide. 

Using data effectively is the key to competing in today’s world as customer expectations continue to rise. Moving from a best guess mindset to a data driven organization requires a significant shift throughout the organization in terms of technology, processes, and culture. Your organization is not alone — many organizations struggle to move towards data as the cornerstone of their organization. 

Here are five challenges that you need to overcome to become a data leader:

Bad data governance 

Your insights are only as good as your data. If your data is full of errors, missing information and duplications, then your results will not be accurate. Your organization could make an inaccurate decision with significant consequences based on faulty or missing data. Your company’s data success depends on your data governance, which is how you ensure your data is clean, accurate, and easy to use. However, many organizations either do not have data governance programs or the business participation an effective program requires. 

By using data mesh, you move true data ownership to the business units, which improves the quality. Data now becomes a product. The data mesh platform manages all of the security and governance, meaning that your insights are based on high quality data, thanks to the data observability and data cataloging capabilities within the platform. That facilitates data  governance process automation which improves productivity as well as accuracy. 

Data silos

For accurate cross-functional insights, a high percentage of the data from the organization might be required. However, many organizations have data silos, for instance when each department’s data is historically stored in disparate locations. Additionally, structured and unstructured data is often separate. By using a data platform that combines all data and creates a single view, your data provides the complete picture of your organization. By eliminating data silos, your data insights enable smarter and more accurate business decisions. 

Lack of skills 

Many organizations do not have on-staff data scientists due to expense or availability. If your organization lacks such skills, here’s what to do: employ technology that enables your data analysts to attack data science problems without necessitating a degree in statistics. That means an easy to use machine learning interface and open source, license-free machine learning algorithms. There are literally hundreds available including large language models which are all the rage. Such a strategy builds data science skill with the advantage that your data analysts already know their data domains, shortening the time to value.

Lack of real-time data

Creating a data-driven organization often requires near real-time data. If you set up an automation for sales contracts, you need the latest information about customer status and pricing — not yesterday’s data. Real-time data also allows you to create personalized customer experiences, such as customizing the offers and information on your home page. Additionally, using IoT sensors for automations is only possible with the ability to collect and manage real-time data.  

Using real-time data starts with using cloud-based technology, such as hybrid cloud. By replacing legacy infrastructure, employees and sensors can access data from any location and see the latest data. Next, your organization should turn to a data platform that provides real-time data analytics and insights. Your organization can then make quick decisions based on the most up to date information possible. By operating on real-time data, your organization can have a competitive advantage over other organizations through insights, personalization, and automations. 

Legacy infrastructure

Becoming a data leader is challenging, if not impossible to achieve, if your organization is using outdated legacy technology. Outdated technology causes many of the other challenges that keep you from becoming a data leader — need for specialized skills, data silos, and lack of real-time data. While on-prem legacy technology certainly has its place, by moving toward a modern private cloud or hybrid alternative where possible, your organization has access to the data that you need to make the right business decisions and create the personalized experiences that customers expect. 

Some organizations get frustrated and abandon their efforts for using data. By instead using a data platform, such as Cloudera, your organization can overcome these common challenges with using data. With the right tools and processes, your organization can begin moving towards becoming a data leader. 

Ready to become a true data leader? See how to take the next steps and get there fast. 

Shayde Christian
Chief Data & Analytics Officer
More by this author

Leave a comment

Your email address will not be published. Links are not permitted in comments.