The architectural components of today’s data architectural world are:ĭata standards are the overarching standards of a data architecture, which you apply to areas such as data schemas and security. Grants all teams the ability to make data-driven decisions.Ensures a system is in place to secure the data.Offers protocols by which data moves from its source to being analyzed and consumed by its destinations.Creates a better understanding of the company’s data.Gives a fuller picture of what is happening in the company. If agility is what is needed to avoid collapse during slow seasons or to capitalize on the spontaneous popularity of a new product, the more advanced the data architecture is, the more capable the company is to take action. The data architecture is 100% responsible for increasing a company’s freedom to move around the world. Streaming data from a set of point-of-sale registers to accounting is another kind of architecture.csv on a local hard drive and reading the file into Tableau on a person’s computer for analysis is a very simple kind of data architecture. Picture these different data architectures: An advanced architecture can make that pawn a queen. If a company were a chess piece, the data architecture defines the moves the company can make on the board.Ī primitive architecture allows your company to move like a pawn. What is data architecture?ĭata architectures will define a company’s livelihood. The writings and how-to’s and best practices are there to share the architecture and help get organizations moving towards it. The world is jumping aboard this framework. A particular kind of data architecture can actually enable agility, so you can meet these business demands.ĭata architecture is critical to the success of a business (and why we’ve written extensively on each data component). Data architecture supports agilityĪgility allows your company to adapt quickly to the business environment and industry. It is the “how” when implementing a data strategy. The goal of any data architecture is to show the company’s infrastructure how data is acquired, transported, stored, queried, and secured.Ī data architecture is the foundation of any data strategy. Automated Mainframe Intelligence (BMC AMI)ĭata architecture is a framework for how IT infrastructure supports your data strategy.Control-M Application Workflow Orchestration.Accelerate With a Self-Managing Mainframe.Apply Artificial Intelligence to IT (AIOps).Our goal is to unburden customers end-to-end in their data journey. Our proposition starts with architecture and we supplement it with engineering, data science, visualization and the necessary governance. For freelancers we offer a long-term contract at a competitive rateĪt DataSense we focus on data integration projects, often supported by Data Vault and automation.An attractive salary package reflecting your expertise, including benefits such as a company car, insurances, communication package and laptop.Extensive training through our DataSense Academy.A positive work atmosphere and a strong team spirit.A stimulating environment driving you to discover new horizons.Being part of an innovative company with talented colleagues working on challenging projects.Data Vault 2.0 experience is advantageous but not essential.Cloud database experience such as Snowflake, Synapse and Google BigQuery is advantageous but not essential.Knowledge of columnar and NoSQL databases, predictive analytics, data visualization, and unstructured data.Able to understand established data management and reporting technologies.Good knowledge and experience in data modeling and design.Data architects must understand the system development life cycle, project management approaches, requirements, design and test techniques Knowledge and experience in systems development.You will translate business requirements into technology requirements and define data standards and principles. Do you have a passion for aligning the data environment of an organization with their strategies?Īs a Data Architect you will visualize and design an organization’s enterprise data management framework, aligned with enterprise strategy and business architecture.
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