The Open, Collaborative Data Platform Transforming Organizations Today
Organizations today have a great deal of untapped or under-used resources in the form of their data. Most are aware of this fact but lack the ability to take coherent action. Siloed data leads to siloed usage so sales teams, for instance, may well have the tools to leverage their information stores (perhaps from CRMs or legacy databases) and use their learnings to improve practices. But collating all available data and using it proactively across the enterprise is no easy task.
Even at the earliest stages of any data-based project, dedicated data analysis teams find themselves expending resources connecting disparate data sources: manual exports, file stores, legacy applications, and many types of static resources. Even after compiling a basic catalog of data sources, new applications and services coming online in any part of the enterprise may not be integrated dynamically into data sets.
Normalization, de-duping, and data transformation rely on individual expertise in scripting, Python, or manual examination — it’s easy to miss patterns and relationships between schemas, especially when an analyst or data engineer has been tasked with a specific purpose or outcome by a decision-maker. Getting the overview is difficult if data irregularities prevent good quality data rules from being formulated.
There are also issues on a practical note that prevent Data teams from reaching their full potential. Data storage, duplicating test datasets for testing, safe access to sensitive information — even internal politics — can impinge on outcomes.
As part of our ongoing series on data analytics, we’re looking at platforms dedicated to helping organizations collect, transform, and present actionable insights into their digital assets. Some vendors have developed a reputation for one or perhaps a few of the data analysis workflow areas of ingestion, storage, processing, preparation, and reporting. However, a new generation of data platforms can provide a single point of reference for analysts and a significant level of reporting and insights for non-specialists. It’s these platforms that we are currently covering.
As companies realize the existence of the virtual gold mines they are sitting on, many rightly dedicate computing resources to mining and transforming information. However, that can soon escalate as the value of data is realized, so many find that IT resources are being allocated away from core business needs. With finite resources, the logical solution would be to place data processing and analysis off-site. The Trifacta Data Engineering Cloud is a fully cloud-based solution that delivers consumable data for advanced analytics and machine learning. Trifacta provides high-quality, transformed data that’s ready to be leveraged by a range of stakeholders to profile, prepare, and pipeline data at scale.
Trifacta is dedicated to the concept of consumable data — that means reliable information (in that it is verified and clean) and actionable. It intelligently transforms digital assets from across the enterprise and creates a live cloud environment where amalgamated and transformed data can be addressed. Both dedicated data professionals and business stakeholders can process and transform complex data sets, using whatever tools happen to be most convenient: from manually constructed SQL queries, through powerful low-code, drag-and-drop GUI.
The platform is designed to be a collaborative space where data professionals and business-focused decision-makers can come together to work with the organization’s greatest asset – data.
Trifacta’s intelligent solution is backed by machine learning that can identify specific attributes and schemas of data sets and display them to operators, ensuring clean data profiles and drawing information from just about anywhere — it’s platform and cloud-agnostic.
Large data sets can be qualified using adaptive rules, which are attenuated by the data itself — the learning corpus is therefore ever-expanding, with iterative improvements in accuracy over time. Obviously, with input from colleagues outside data analysis teams, the refining process remains business-focused, ensuring results are always actionable by the enterprise at large.
Fully automated data pipelines developed over time produce insights and analytics capable of transforming the organization’s information assets, using fast and resource-friendly cloud-native processing. As a cloud-only service, Trifacta is being used by thousands of companies worldwide to improve data quality for operational excellence and getting better ROI on data investments.