Using Generative API for Better Data Quality in Databases and Files

Cloud Data Usability Platform - Business Case for Better Data

Data: A Strategic Asset and a Competitive Advantage

Long gone are the days where the organizing of data was just a component of managing a business. Now, the explosion of data and the ever-growing connected Web infrastructure have accelerated the proliferation of analysis tools and business processes that leverage these trends. This enables businesses and organizations to seek and realize positive outcomes from the effective harnessing and utilization of their corporate data assets. For example, cultivating data as a strategic asset can provide the following:

- Deeper insights into your organization
- More informed decision-making
- The discovery of new opportunities
- Revenue maximization
- The measurement and optimization of performance
- Increased customer engagement
- Customized communication
- An acceleration of innovation
- Cost control enablement
- Early identification of organizational issues
- Risk mitigation
- Efficient operations at scale
- And much more...

Product categories such as Analytics, Artificial Intelligence, Machine Learning, Business Intelligence, Data Science, and dozens of others have emerged around the unleashing of data as a competitive advantage, with seemingly endless products available in every category. Yet, very little attention is often paid to the actual data content that serves as the foundation of these applications, including data preparation, data availability, ease of access, data completeness, data accuracy, data consistency, data usability, elimination of data redundancy, and fitness of purpose.

That's where Interzoid comes in...

Leveraging Three Emerging Trends

Three trends have emerged over the past few years.

APIs, an acronym for Application Programming Interfaces, are accelerating their presence on the Cloud exponentially. They are helping machines, applications, Websites, and tools to connect and communicate with one another. The key has been to standardize this communication through various agreed-upon protocols, allowing interoperative data exchange regardless of underlying hardware, operating system, or application. However, while the communication has been standardized, the actual data payloads delivered by these protocols have not. Those experienced with using data delivered via API understand that it can arrive in all sorts of shapes, sizes, and formats making it difficult to make use of, much less combine with existing data for analysis purposes. This contributes to the challenges described above, and makes the goals of data-centric organizations seeking data-driven outcomes much more challenging.

Cloud Data Platforms have also emerged at a lightning pace. Platforms like Snowflake, AWS RDS, Microsoft Azure SQL, Google Cloud SQL, CockroachDB, SkySQL (a Cloud-based version of MySQL), implementations of Postgres on the Cloud, and a long list of other platforms are enabling organizations to leverage Cloud infrastructure to host and manage their data assets far more efficiently and cost-effectively than ever before. This has in turn accelerated an incredible rate of movement of data to the Cloud, creating the foundation for an entire new era of data-driven computing and machine-delivered intelligence.

Meanwhile, Artificial Intelligence is gaining momentum at breathtaking speeds enabling monumental breakthroughs in data analysis. Components of AI such as Machine Learning and Natural Language Processing are enabling models to be created and fed into data analysis products that will soon make correcting enterprise data assests to be as effortless as correcting text conversations and search queries on your mobile device.

Interzoid sits at the confluence of these trends, using APIs to seamlessly and without friction, deliver external data payloads to an organization's Cloud data assets, analyzed, corrected, and otherwise refined using various Machine Learning and Natural Language Processing techniques.

This is not only relevant to raw third party data acquired for the purposes of augmenting internal data, requiring you to then try to make it all work together with internal systems, struggling through all of the challenges outlined above. Instead, you can leverage our capabilities to first improve the value of the data you already have within these internal systems at the data content level, and then enabling it to be combined and enhanced with, and only with, the data you actually need, all with ease of access, data consistency, data usability, and elimination of redundancy built right in.

APIs, Cloud Data Platforms, and AI/ML-driven data analysis are the future of an organization's competitive intelligence. Interzoid is the nexus between all three. We can help you achieve a foundation of high quality, comprehensive, efficient data to create an empowered, data-savvy workforce. This will pave the way to obtain the extraordinary outcomes for an organization that an effective data asset strategy can provide.

Example Cloud-Native Data Engineering Use Cases

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