Data Architecture

We are fluent in building a modern Data Architecture

Without a well-planned, careful, deliberate approach to data architecture, another type of architecture rises to take its place—a “spaghetti architecture”

Modern data architecture doesn’t just happen by accident and the act of planning modern data architectures is not a technical exercise, subject to the purchase and installation of the latest and greatest shiny new technologies.
It is much more than this, it is an uplifting process that brings in the whole enterprise, stimulating new ways of thinking, collaborating, and planning for data and information requirements.

The old models of data architecture aren’t enough for today’s business demands and the amount of data generated. An architecture based on simply moving data from Production to Datawarehouses is not enough.

The following is what you should consider on designing a modern Data Architecture

Pilars of modern architecture

IDENTIFY THE TYPES OF DATA THAT ARE THE MOST VALUABLE

To be of value, information needs to have a high business impact. Work directly with business to unsure what type of data are most valued.Today’s open source and cloud offerings enable enterprises to pull and work with such data in a cost-effective way.

MAKE DATA GOVERNANCE A PRIORITY

The process of identifying, ingesting, and building models for data needs to assure quality and relevance for the business.

Responsibility for data must be established—whether it’s individual or collective.

BUILD SYSTEMS TO CHANGE

If a new solution comes on the market the architecture should be able to accommodate it.

The types of data coming into enterprises can change, as do the tools and platforms that are put into place to handle them.

DEVELOP A REAL-TIME ARCHITECTURE

A modern data architecture needs to be built to support the movement and analysis of data to decision makers and at the right time it is needed.

POSITION DATA AS A SERVICE

Data as a service is by definition a form of internal cloud, along with accompanying data management platforms, tools, and applications—are made available to the enterprise as reusable, standardized services.

OFFER SELF-SERVICE ENVIRONMENTS

With self-service, business users can configure their own queries and get the information or analyses they want, or conduct their own data discovery, without having to wait for their IT or data management departments to deliver the information.