Best Practices for Data Ingestion

Businesses need to refine their operations continuously so they can provide better customer service, innovate new products or services, and stay competitive. One way to do this is through data-driven decision making which leads to smarter and more informed choices and ensures that a business is taking into account the needs and behaviors of stakeholders and customers. 

But with mass volumes of data being collected daily, it can be difficult for businesses to keep up and make sense of it all. One of the first steps in an effective data analytics structure is data ingestion – the transportation of data from multiple sources to a storage medium where it can be accessed, used, and analyzed. Whether through in-house teams specializing in data science or a third-party providing insight services, data ingestion is one of the most effective ways for an organization to manage large influxes of information. 

So how is data ingestion done and how can businesses leverage it to their benefit? Keep reading to learn a few best practices for effective data ingestion. 

Data Ingestion Methods

Data ingestion can be performed in various ways but there are three methods that stand out:

  • Batch. In the batch approach, data analysts collect and shift data at certain times. This is a good option for processes that occur regularly at predetermined times such as weekly or daily reports. 
  • Real-time. Ingesting in real-time, also known as streaming, is the best way of collecting time-sensitive information. In this process, data gets retrieved, processed, and stored in applications that render visualizations as events happen. This method is what companies use for making high-level decisions.
  • Lambda architecture. This is a method that combines real-time and batch procedures. This strategy combines the advantages of the two methods; making use of real-time ingestion to extract information from time-sensitive data and batch ingestion to provide a broad view of recurring data.

Data Ingestion Best Practices

Data is an ever growing asset in the corporate world today, and increasing exponentially on a daily basis. As a result, most businesses have multiple data sources they need to pull from. To maximize all of this data, companies need to make sure they’re ingesting them properly before they’re stored and processed. Otherwise, the company could miss out on crucial insights. 

One way to ensure that businesses ingest data in time is by putting infrastructure in place and adding resources for data management. Using artificial intelligence, anticipating challenges and planning ahead, and leveraging automation are some ways to support a growing enterprise.

  • Automated Ingestion

As an organization grows, so too does the amount of data that needs to be processed and stored. At some point, manual techniques that worked for smaller volumes of data will no longer be effective or sustainable. This is where automation comes in. Automating processes along the way of data ingestion can increase productivity, minimize downtime, and save time on processing data. What’s more, automation makes your IT architecture consistent, reduces human error, consolidates information, and keeps data safe.

  • Plan, Plan, Plan

The goal of any data analysis is to turn raw information into insights a company can use. When your data volumes increase or you start collecting multiple types of data, your methods for analyzing will grow complex. Data ingestion is one big process that can help you anticipate these types of challenges and plan accordingly to ensure your data processing runs smoothly and efficiently. 

  • Leverage Artificial Intelligence

Manual interventions in the ingestion process causing slowdowns, lost time, and redundant work. But employing digital operations and AI using statistical algorithms and machine learning can minimize (and can even eliminate) the need for human interventions during the ingestion process. With AI, you can increase your accuracy levels, save time, and get to actionable insights quicker.


Effective and streamlined data ingestion is a must for any business dealing with large volumes of data. By leveraging this process and employing best practices such as automation, smart planning, and using AI, businesses can effectively manage their data ingestion to make better decisions and optimize outcomes. 

If your business is looking to simplify and improve its data processes, reach out to Gemini today. We can solve the biggest data challenges, enabling you to understand and share data stories. We help organizations construct a connected view of their business by connecting the dots between data from disparate sources. Go from data to insights in no time.

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