Data Trust and Reliability Issues Impact Business Analytics

Cloud analytics drives innovation. Increased processing power, cheap storage, and in-memory computing have made it possible to churn through massive volumes of data in virtually no time at all. Business analytics vendors compete to provide the fastest, most intuitive tools with integrated visualization capabilities. Cloud hyperscalers provide the kind of highly elastic platform ideally suited to analytics with the necessary capabilities such as scalability, security, and computing power already in place.

Today, the big challenges of business analytics lie with the data itself. The volume and variety of available information stagger the mind. As businesses strive to tap into the enormous value of all that data, many face a common challenge. It starts with organizing and aligning disparate datasets from internal sources while trying to keep data quality and data integrity levels high. But to approach the true potential of advanced business analytics, companies must look beyond internal systems and use data enrichment techniques to build out datasets that reflect the full context and richness of their domain.

Whether that’s a retailer striving to understand foot traffic in a particular location, an insurance company searching for factors to better understand risk, or a public transport agency seeking to improve its services, they all face a similar challenge. How can they best procure reliable and trusted datasets for business analytics?

The Power of Mobility Data

The volume of available data continues to increase as mobile phones, IoT devices, and smart machines proliferate.  Mobility data comprises an especially rich resource, provided that business leaders know how to take full advantage of it. Although the vast amount of data flowing from mobile devices can be overwhelming, those successful in mastering the tidal wave of information gain business insights that drive a clear competitive advantage.

Data preparation remains a top priority for many. In its recent Data Integrity Trends report, Corinium Intelligence found that data and analytics professionals spend an average of 40% of their time on data cleansing, integration, and preparation. At some companies that number reaches as high as 80%. Without a strategy to manage these tasks at scale, many of those businesses will find themselves falling further and further behind, unable to keep up with the accelerating wave of new data.

To keep up, companies must look to automation. They must adopt scalable data quality tools that proactively discover and catalog data, identify anomalies based on clearly defined business rules, and generate workflows to alert users to the need for issue resolution. To scale, businesses need to manage by exception. Otherwise, they’ll be consumed by their efforts to keep up with the data onslaught.

Trusted Data Enrichment with Mobility Data

A key challenge with respect to scale is effective data enrichment. Businesses with access to a growing volume of data from mobile devices must be cognizant of privacy concerns and regulatory scrutiny. Because it is associated with time and place, mobility data also opens the door to an array of new data points about populations, the activities they engage in, and the timing of those activities.

Consider some of the use-cases for data enrichment with information from mobile devices.

Data Enrichment in Retail

Retailers can gain a detailed understanding of the types of customers visiting a particular location, including demographic profiles, income levels, and lifestyle preferences. They can gain insights into the variability of foot traffic at different times of the day or throughout the week. This can help them to attract new customers from that existing traffic by offering new products and services that will appeal to those audiences, or presenting messages tailored to a specific demographic.

Mobile data can be used to refine site selection, or to better measure store performance relative to the surrounding foot traffic. Digital display advertising can be tailored to the specific populations present throughout the day, enhancing the effectiveness of mall signage, billboards, or display advertising in any other dynamic high-traffic location.

Data Enrichment in Insurance

Mobility data is driving value in the insurance industry as well, where it is already being used to price policies based on usage.  By tracking the volume of visitors to a commercial location and the length of the average stay, insurers can more accurately assess risk and price policies accordingly.

Data Enrichment in Telecommunications

Naturally, telecommunications companies are using mobility data as well, efficiently planning infrastructure investments by developing a thorough understanding of the populations in their areas of service and analyzing how people move about within those geographies over the course of time.

A key element of success in any business is understanding the customer.  Mobility data helps leaders gain insights into their customers and prospects by providing key information about where they live, work, and spend their leisure time.

To do that effectively, they must be able to trust the data.

Data Integrity Defined

Confidence in data-driven insights begins with a holistic approach to data integrity. Data quality is an important component of that, but data integrity encompasses much more than data quality. It is data that is accurate, consistent, and in context to empower your business to build bigger possibilities with your data. Data integrity is built upon four pillars that together ensure a sound foundation for data-driven insights.

Real-time data integration eliminates information silos, ensuring that your data provides a complete picture of what’s happening in your organization. Location intelligence enables an understanding of surrounding people, assets, and trends to determine what opportunities exist for growth or improvement. Data enrichment fills out the picture even further, giving your users curated, prepared, and easy-to-access data to incorporate into business processes for a rich and contextual understanding of customers, markets, and more. Data governance and quality ensure information and processes are managed soundly and meet the necessary standards for regulatory compliance.

These four pillars work together holistically to support data integrity, that is data quality and governance, integration, data enrichment, and location intelligence. When an organization tends to of these pillars, trusted insights follow. Users can have confidence in the results.

Data Enrichment at Scale

According to Chief Data Officers surveyed for the Corinium Intelligence Data Integrity Trends report, data enrichment at scale is a challenge. A majority cited concerns about compliance, especially with respect to GDPR and similar privacy regulations. Half cited concerns about the quality standards of externally sourced data, and nearly as many expressed reservations about the interoperability of third-party information. Another key concern was the frequency with which externally sourced data is updated.

Mobility data is especially challenging because of the spatial relationships that come with it and because the granularity of precision is so widely variable across different datasets from different vendors. As a leader in location intelligence, Precisely offers a unique advantage in this respect. By assigning a unique identifier to every location, Precisely can unlock thousands of new data points about any given location. This identifier, called the “PreciselyID”, links any geographic coordinates to a world of new information.

By combining that capability with Precisely’s far-reaching expertise in location intelligence, you can bring a wealth of new context to existing datasets. For mobility data, that includes curated information sourced from millions of mobile devices, but without personally identifiable information (PII) attached. By focusing on the dynamic movement of populations, Precisely can provide a rich context to drive valuable insights, without raising concerns about the privacy and security of PII.

Precisely’s Dynamic Demographics offers mobility data as a turnkey service, making large, complex datasets easy to consume and use in the system of your choice.

If your organization is aiming to leverage mobility data more effectively, then Precisely can help. To learn more about how our Dynamic Demographics data can help your business analytics download our free ebook: Human Mobility: Why Understanding Populations and the Way They Move Has Become Critical.