“Information is just bits of data. Knowledge is putting them together. Wisdom is transcending them.”
Stratacent can help you extract actionable insights from your to make intelligent business decisions. We leverage data governance best practices to ensure quality, availability, integrity, usability, consistency and security.
To meet today’s ever-growing demand for data and analytics, organizations often augment their data with third-party information to get better insights. Stratacent can help you with data enhancement and enrichment using various tools and business rules to merge and augment the information.
At Stratacent, we follow the typical data lifecycle process, which starts with discovery. Stratacent can help you with data mining and identification. When using tools such as SAS Enterprise Miner, it is critical to understand the “what, where, and why” of your data. These insights are then coupled with classification, which is the main pillar behind the security and privacy of the information.
Stratacent can help you ensure quality, which is the primary goal of any data governance project. Whether these are applied at the source, or during the ETL process as the data get integrated into a data warehouse, we can help capture quality requirements and implement those rules. Our strong practice around automation complements our data quality implementation.
Stratacent as Your Data Steward
One of the first steps in data governance is identifying a steward to manage the process. As the steward for our customers, Stratacent uses integration and virtualization to present a unified front. We then provide the analytics and reporting tools for traditional analysis, AI, machine learning, and more.
If you have already started your journey to the cloud, then migration and storage is your top priority. Our Cloud Infrastructure practice can help you create analytics bundles to support taking the analytics to the data. We can help you with migration strategies for both structured and unstructured data.
The Stratacent model uses what we call “data gravity,” which means your analytics environment is defined according to your data, not the other way around. We streamline the process by taking your analytics to the data instead of vice-versa.