5 fundamental questions for your data journey
To accelerate its journey to AI, a data-driven organization needs a trusted data foundation that empowers information stakeholders. Stakeholders need the ability to discover, understand, integrate, analyze, govern and self-serve structured and unstructured data — on premises, on cloud, and hybrid — at any scale.
Chief analytics officers need to crunch external and internal data to make predictions on business opportunities and threats, sales performance, revenue projections, and data exploration on new solutions or connections buried in data.
Chief marketing officers need customer data that is current, trusted, and complete encompassing 360-degree view on everything about them.
Data scientists require clean data to focus on their modeling versus wasting time on data hunt, cleanup, munging or integration.
Data-driven, proactive and innovative organizations are meeting the needs of all these information stakeholders. They started by asking five fundamental questions in their data journey:
- What data do we have?
- Where is that data located?
- What systems are using that data and for what purposes?
- Does the data meet all regulatory and compliance requirements?
- How can we gain agility through data to reduce risk, reduce cost, and make money?
The journey to AI
After answering these five fundamental questions, what insights were derived? Data driven organizations:
- Discovered all the data they have, which can start with smaller scope on a given business need
- Defined common metadata and business terminology across the organization to have agreement on what information means
- Found metadata on common policies and plain-language rules on how it will be used
- Defined data quality levels, set rules for monitoring the data quality and build data lineage to increase users’ confidence in the data
- Realized the need for the right tooling for data architects and data engineers
- Used data integration and replication to help make sense of a myriad of data sources to optimize their data warehouse environments
- Governed their data lake from the start
- Paid attention to every detail of their customer or product data
- Deepened their customer relationship and intimacy in every customer touch point
- Made trusted data the front and center of business digitization and digital transformation
These discoveries require clear agreement on how information assets will be maintained, monitored, used, archived, put on hold when needed and disposed of when it reaches its end of lifecycle. Organizations must also set enterprise and departmental standard practices for securing and protecting strategic information assets and create rules to govern how information is shared, protecting sensitive information.
Through these journeys and discoveries, data-driven organizations may gain a competitive advantage, adapt to market changes faster and disrupt instead of being disrupted. Lastly, but most importantly, the inherent opportunities reduce cost, mitigate risk and make money.
The results are in. See what companies are saying their main focus for their information architecture is in 2018 by reading “Data Integration Hits Inflection Point.”
Watch Rob Thomas break down how IBM helps build a trusted analytics foundation.