Organization-level strategy guides comprehensive analytics engagements managing data residing within and outside the organization. Simply consolidating organizational data for a single analytics initiative may be sufficient for organizations that are interested in achieving ad hoc results. Unplanned analytics initiatives with a weak data strategy can only provide limited business value.

Organizations with large scale analytics engagements consider how data is acquired, stored, and used in a planned way. Multiple components influence the data strategy, including end-to-end enterprise data architecture, storage capabilities, data privacy, and data governance policies driving data life cycle within the organization. As more and more data sources start residing outside the control of the analytics team within the organization, policies directing the data integrity, consistency, relevancy, and other quality parameters are established.

Similarly, data gateways from devices such as the internet of things (IoT), sensors, business applications, and business processes are established for data storage in cloud environments. When the volume and velocity of data acquisitions increase, as in the case of streaming data, or the number of analytics initiatives increase within the organization, keeping track of an organization’s data and data requests becomes a complex activity. In the absence of a single source of truth, a just in time approach, or a self-service strategy can be employed to cater to data needs within the organization.

An organization-level data strategy may include the following planning considerations:

• Data governance: the rules and policies that manage the data assets of an organization to ensure high-quality data.
• Data architecture: the models and standards that govern how data is collected, stored, and integrated across an organization.
• Data security: the activities performed to protect data from a privacy and confidentiality perspective.
• Metadata management: the administration of information that is maintained about the data assets an organization collects and manages.

When formulating a data strategy for an organization, technical professionals take inventory of the existing environments. All planning considerations align with a strategic goal and a future state applicable to the organization. Business analysis professionals bring this strategic perspective to the forefront and collaborate with IT and the business to design an end-to-end strategy for data and analytics.