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Data products can take many forms, from run-of-the-mill spreadsheets and databases to more complex software applications and machine learning models. These applications and models then analyze data in real time or process large sets of historical data to derive actionable insights that data teams and business leaders can use for better decision making. Data is clearly valuable, but effective data products create data usability – provided by visualizations, charts, and graphs across interactive dashboards for users – that give an organization’s data even more value
Large enterprises, SME/SMBs, government agencies, and other organizations are using data products to make more informed decisions and gain competitive advantages. As technology continues to advance and mature, data products will become more efficient and will be applied to increasingly solve complex problems.
Who Uses Data Products, and Why?
Data products are used by a wide range of organizations, individuals, enterprises, governments, and researchers for various purposes, which include the following examples:
- Businesses use data products to expedite decision-making, improve operations, and gain a competitive advantage. These data products may be in the form of AI-powered insight engines, or business intelligence dashboards. For example, a retail company may use data products to analyze customer purchase patterns and optimize inventory management. And a financial institution may use data products to detect fraudulent activity or assess credit risk.
- Governments employ data products to streamline policy-making, track departmental performance, and make public services more efficient. A government agency may use data products to analyze crime data and inform public safety strategies. A national statistics agency utilizes data products to track economic indicators and help formulate economic policies. On a much more macro level, the United States government also provides a long list of open-source data platforms to validate the quality and accuracy of various departmental data. The JSON Validator program provides a platform for agencies to validate their data against required federal metadata schemas.
- Researchers use data products to analyze large and complex datasets, test hypotheses, and generate new knowledge. Take the case of scientific research in the field of genetics. The arrival of Next-Generation Sequencing (NGS) technologies is currently helping scientists hasten research initiatives and drive down costs. Using Big Data alongside multiple cloud technologies, clinical-grade genomic tools or software have managed to accurately detect and categorize gene variations associated with a range of cancers and hereditary defects. The same technology was also employed to detect the presence of the SARS-COV-2 virus within human cells during the recent global pandemic. On the other hand, social science researchers utilize survey data to better understand the quality of life and other such social phenomena.
- What about us, the public consumer? General public users use data products in multiple and diverse forms. We may use personalized finance apps to help us track our spending and manage budgets, or personalized video/audio streaming applications like Netflix and Spotify, which use data to recommend content that users might enjoy.
Why Build Data Products?
Data products are used by a wide range of individuals and organizations across various industries. From small businesses looking to better understand their customers, to large corporations analyzing complex data sets, data products are essential for making data-driven decisions. As data continues to play an increasingly important role in the modern business world, the use of data products will only continue to grow. Therefore, it is important for businesses and individuals to stay up to date with the latest data products and technologies to stay competitive and make informed decisions.
Acceldata’s multi-layered data observability solution enables enterprises to gain comprehensive insights into their data stack to improve data and pipeline reliability. This helps business teams to build and operate great products by monitoring compute performance, spend efficiency, and delivering reliable data efficiently.
Learn more about Acceldata’s Data Observability platform to learn more about how we can help you do the same for your business.
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