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Now, a first of its kind data integrity suite to address data accuracy issues

Lack of data integrity is a critical problem for businesses today. And with more and more enterprises including aspects of location data in their records — where customers live and work, as well as their mobility, or the locations of suppliers and their facilities — and increasing their intake of descriptive and demographic factors about particular locations, it becomes increasingly important for location data to be precise and correct. In this background, Precisely’s Data Integrity Suite, launched today, is the first of kind to enhance accurate, consistent data with context from location intelligence and data enrichment. With worldwide spending on digital transformation expected to reach $1.3 trillion this year, the Precisely Data Integrity Suite seeks to establish a foundation of trusted data to ensure these investments are successful.

The product is the first from the company which was formed after Syncsort’s acquisition of the Pitney Bowes Software & Data business in December 2019. In May the company rebranded as Precisely to reflect its ability to power confident business decisions through maximum accuracy, consistency, and context in data. Earlier this month, Precisely announced the sale of its Confirm business unit, acquired in the transaction from Pitney Bowes, to enable greater focus on, and accelerate development in, its core data integrity capabilities.

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Why data integration is important

Global trends such as working from home, increasing volatility and unpredictability, and supply chain disruptions are casting a spotlight on how well organizations are embracing the transition to a digital enterprise while minimizing threats to business continuity. Data enrichment along with location context has become imperative to provide insight and visibility into day-to-day operations and for communicating effectively with employees, customers, and the entire supply chain. Enhancing data with context helps surface hidden connections, creates meaningful relationships and ultimately makes data more valuable.

Location awareness has become paramount in contact tracing and proximity analytics. However, it is also observed that most organizations do not capture locations with consistent formats. For example, it would be a challenge for many companies to map their supply chains in a way that allows for risk review in a location-based context. This requires a layer of data intelligence that places the enterprise’s data into a larger context, including knowing what data means as well as where it came from, how to use it, enriching it where it makes sense for business processes, and aligning it with relevant location(s). This is where the data integrity suite could prove valuable.

“Ensuring data is complete, compliant, and accessible is no longer enough to keep pace in the digital economy. Today data integrity is the business imperative; businesses must maximize accuracy, consistency, and context in data to know they can trust their data-driven decisions,” says Josh Rogers, CEO of Precisely. “Decisions made on flawed data or gut instinct destroy value. With our unmatched, proven capabilities, the Precisely Data Integrity Suite enables our enterprise customers to achieve data integrity and move forward with confidence.”

Location data is no more for just verifying addresses and traditional GIS analytics. Today, realizing the spatial context in which interactions and transactions take place are increasingly being used to derive greater value from data that had previously been used to plan and analyze activity. Location data and intelligence is emerging as an important tool in areas such as contact tracing, precision agriculture, and smart emergency management. As location is incorporated into more business processes, it becomes increasingly important that the location data be precise and correct. For example, as the volume of ecommerce packages increases, the importance of shipping packages to the correct and validated customer address increases.

The suite provides differentiated capabilities across the full spectrum of data integrity with deep expertise in integration of even the most complex data, connecting today’s infrastructure with tomorrow’s technology. It is capable of powerful data profiling, smart matching, and entity resolution to ensure data quality with context graphs to reveal hidden relationships and patterns in data, and is capable of providing hyper-accurate location insights for both operational and analytical use cases, delivered with unmatched scale and performance. The suite has curated location, business, and consumer data with more than 9,000 attributes for data enrichment, consumable in a modular fashion, the suite enables customers to choose from key capabilities to advance their business without a costly investment in a monolithic platform. Built with the first principle of “design once deploy anywhere,” the suite can be deployed on-premises, in the cloud, or in hybrid environments. APIs enable clients and business partners to develop new solutions to data integrity challenges.

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Data integrity is an issue

In an IDC survey conducted this year, nearly half of the respondents indicated that a general lack of trust in data quality is a challenge for their organization, and 56% of respondents indicated that lack of trust in the results or outputs of data analysis is also a challenge. As much as 84% of CEOs do not trust the data on which they base decisions, 68% of organizations are hindered by siloed data, and nearly 47% of all new data records contain at least one critical error. Despite these realities, companies continue to make large, transformative bets in search of digital advantage.

IDC estimates that enterprises were responsible for over half of the 45 zettabytes of data that were created in 2019, with 88% of that data being replicated, 60% of it distributed, and 19% of it created and consumed in real time.

IDC’s June 2019 survey found that 95% of data integration software user organizations were integrating up to 6 different types of data across 10 different types of data management technologies in hybrid cloud environments. It also observed that inefficiency and diminished effectiveness of data-native workers was another symptom of complexity and lack of data integrity.

Data silos continue to exist and to grow as hybrid cloud distributes data between on-premises and multi-Cloud environments, according to IDC. In 2019, 95% of organizations were integrating data across hybrid cloud environments, and IDC expects that number to be closing in on 100% because cloud migration has accelerated in recent months. Data silos create not only data divisions but also data context divisions.

“The market is screaming for data it can trust. Digital initiatives that once showed such promise can’t get off the ground, with bad data stalling omnichannel experiences and impairing predictive modelling efforts. AI and Machine Learning have unlimited potential to advance human progress and quality of life, but if we train our models with flawed data, they’re getting a bad education,” said Eric Yau, COO of Precisely. “Achieving data integrity enables us to trust the data-driven decisions made by both people and machines because they are made with maximum accuracy, consistency, and context.”

According to IDC, “Data is a core element in the future of intelligence, but it can also be an inhibitor to success. The current state of data cleanliness and quality, intelligence about data, and lack of context are impacting the organization’s ability to integrate and synthesize information, restricting the organization’s ability to learn from and use the data, and limiting the scale at which insights can be delivered for better, faster, and more confident decision making.”

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