How To Build a Data Pipeline for Better Decision-Making

How To Build a Data Pipelines for Better Decision-Making

Data pipelines help enterprises collect, organize, and disseminate information to help employees make decisions. Collecting the data is easy, but moving it becomes a challenge as obstacles that slow and corrupt its flow get in the way. 

Fortunately, solutions exist to move data for effective and timely decision-making. Enterprises can build their structures or incorporate real-time data streaming from providers like Striim. Data pipelines need some additional components. 

Ask questions before building

Before investing in a data pipeline, decision-makers should ask several questions to determine what they need. 

  • What is the purpose of the pipeline?
  • What does the data need to accomplish?
  • What data will move through the pipeline
  • Who needs to access the data? 
  • How will you store the data?
  • How much data needs to move through the pipeline?
  • Where do users need to access the data? 

Knowing the data pipeline’s who, what, when, where, and how helps enterprises focus resources effectively while building their data pipelines. Enterprises also need to determine the speed of data processing and whether they want to integrate other technologies into the channel. Some enterprises need their data to work with microservices or move off-site to their partners. 

Query capability with low event latency

Data products need the ability to allow IT experts to query recent information as it travels through the pipeline. Data scientists use this information for testing and creating useful applications that can update when needed. The data sources should be siloed and available on the cloud for easy access in remote situations. 

Explorative interactive querying

The best pipelines allow users to run large batch queries and small interactive queries. Users need to be able to organize and evaluate data without having to wait hours. Query results should arrive in real-time so users can get real-time information when they need it. Effective data pipelines should have intuitive features rather than overly complicated codes and instructions. 

Efficient scalability

Any effective data pipeline system should have the scalability to meet the needs of growing businesses. As more data flows through the pipeline, the system should be able to store it and offer all data sets to users. 

The data should be available through several sources so users can access it at home, in the office, and on the road. The data pipeline needs to scale to create, rely on, and store data without becoming clogged, overwhelmed, or lost. 

Uninterrupted updating and testing

Data pipelines need to be available at all times. IT specialists should be able to update and maintain the data channels without having to shut them down or suffer data loss. Efficiently structured pipelines should also allow for testing without having the results contaminate the database. 

Wrap up

Moving data through an effective pipeline helps businesses and organizations make better decisions. Companies can lose efficacy when the data clogs in a bottleneck or gets lost in the shuffle of the cloud. Building a better data pipeline involves thorough planning to avoid disruptions and latency.