5 Critical Components for Assessing the Quality of Enterprise Data

One of the most vital business lessons to derive from the ongoing global pandemic is the importance of data quality. While making key decisions around the best ways to rapidly implement and pivot strategies, ensuring you have high-quality data is essential. During this crisis, those who do not have the necessary data needed to steer these critical choices properly have been struggling to put a plan in place.

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From reports and charts to dashboards and tickers, nearly all business leaders consume data daily across verticals. Leveraging quality data enables businesses to manage operations, assess competition, track market updates, and monitor and improve customer experience. Good data drives strategy and priorities, informing risk management and decisions. It can even direct you to shift your entire business approach when needed. But is it the right data? 

In the modern digital transformation era, quality data will illuminate the path ahead, but bad data will stand in the way by obscuring what’s most important. In a recent study, 92% of executives said they are increasing their pace of investments in big data and AI, placing data and analytics firmly at the top of enterprise priorities.  

Whether you need to make a case for data quality or are responsible for implementing it, these five critical components of quality enterprise data offer a helpful guide.

#1: Selecting the Right Information 

For data to drive the right decisions at the right times, it must be the right information to inform action! Deciding internally on the key metrics and performance indicators that will drive business strategy and action is paramount. Next, it’s imperative to have plans in place to execute on that data-driven vision. 

Quality data will inform strategy and drive action, pointing you in the direction of what to do. Yet, too much data or poorly managed data will produce a dense view leading to pitfalls. From manufacturers that rely on data for successful operations of their supply chains to large financial services institutions that count on data to guarantee comprehensive business decision making, Maven Wave provides the expertise to create systems and workflows that manage clean data ingestion and transformation at scale.

#2: Speaking the Lingo 

There are roughly 6,500 languages spoken in the world today, but data is not among them. Globally, as more and more businesses deploy data quality plans from the ground up, there must be a documented definition, data collection/aggregation method, data transformation algorithm, and storage plan. Enterprise leaders must understand this as part of their everyday vocabulary, and everyone needs to be speaking the same data language. 

#3: Representing Relevant Time Frames 

Your data collection and transformation must accurately inform the window of opportunity being considered. For example, while many are still uncertain why there was such a toilet paper shortage as COVID-19 hit, it’s clear that pre-pandemic retail supply chain metrics are not going to help retailers understand how much to stock now. Enterprise data must be timely; otherwise, it’s simply an interesting number. 

#4: Ensuring Accuracy

Not only must your data have the right granularity for your intended purpose, but it also needs to be accurate. Encompassing the right measurement points and methods, your data must represent what you think it represents.

Nothing is ever perfect, and there are so many factors to consider when leveraging data, especially for capacity planning and social policy. If you look at the recent coronavirus pandemic, public health websites indicate a trend in reported new COVID-19 deaths – fewer on the weekends, spikes early in the week. Is that truly because of the disease progression? Or perhaps it’s because some institutions simply aren’t reporting over the weekend, preferring to roll that data into Monday’s report? Complex problems and big data always present these types of issues.

#5: Assessing Data Readiness 

Communication is the key to a successful data quality plan. Data and its variations must be visible, accessible, and widely communicated across your organization. Data and internal communication go hand in hand. While technology continues to evolve, people still deliver results. Enterprises that silo and hoard data for a few leaders or teams are undermined.

Given the pain points that we’ve seen play out publicly with reporting when it comes to COVID-19 and reporting, imagine your organization’s needs and consider your approach. Your data needs to serve you. 

While businesses and the world have changed drastically in the last few months, one truth remains: access to quality data alone is not enough to ensure sound business decision making. At Maven Wave, we help enterprises realize the full potential of their data through comprehensive Data Quality Assessments, ensuring your business is ready and agile for what lies ahead. 

With a multitude of awards and Google Cloud Partner Specializations, including in Data Analytics, our team can build and deploy modern analytics platforms, designed specifically for your needs. Contact us to request your assessment, and download our latest whitepaper, Will your Business Live or Die by Data, to learn more. 

July 1st, 2020
DATA ANALYTICS & MACHINE LEARNING

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2020-08-10T09:55:31-05:00