How to Evaluate the Best Tools for Data Ingestion Challenges?

Data Ingestion

It is the migration of the data from single or different sources to a target area where the data could be analyzed and processed for organizational growth. Data ingestion has become a very crucial task in the cloud. Nowadays, it’s seeing a vast increase as more companies adopt cloud storage instead of on-premise.

This article is mainly focused on the Snowflake Cloud Platform. Let’s understand that first.

What is Snowflake?  

Snowflake is a data warehouse built for the cloud. It is faster and easier to use. Snowflake is a true Saas platform. No hardware or even software installation is needed. Snowflake provides a user-friendly UI (User Interface). Snowflake provides the resources to perform an analytical operation and it allows to store the business data. Snowflake provides the highest level of security. All data is encrypted as well as compressed before loading into the storage layer. It provides a secure way of sharing the data from one entity to another.

Snowflake Data Ingestion:

Snowflake has two types of data loading –

  • Bulk Data Loading
  • Continuous Data Loading

Bulk Data Loading: Bulk loading allows loading the big-batches of data from the file of a specific file format which is supported by a Snowflake. Using the COPY command, bulk loading can be achieved.

COPY INTO target_table_name
FROM @stage_name
FILE_FORMAT = file_format_name

Continuous Data Loading: Continuous data loading allows loading micro-batches of data as soon as they are available on stage. Snowflake provides Snowpipe to achieve continuous data loading. Snowpipe loads data within minutes as soon as files are available on the staging area.

COPY INTO target_table_name
FROM @stage_name
FILE_FORMAT = file_format_name

Why Data Ingestion is Crucial:

In today’s world, data is everywhere, especially in businesses. They need data to analyze and predict future market activities and plan accordingly. Using this data, organizations can understand the user needs, user demands, and user habits. So the organization can make plans accordingly and make their product more superior based on the user needs.

To achieve this, Data Ingestion comes into the picture.

Evaluate the Ingesting Challenges:

The data ingestion challenges are as follows:

1. The process is slow:

As data is fetched from different source locations into the target location, the data from different sources have different formats. The data has to be converted into a standard format. Considering the volume of data and the traffic, it requires a lot of processing time.

2. Identifying the data complexity:

Organizations should understand the data and its complexity. What type of data is the organization working with? As the data is coming from different source locations, they need to focus on data cleaning and connecting to the different data source locations.

3. Size of data & data quality:

Mapping errors, missing values, and incorrect format may lead to compromise in data quality and efficiency. Data should be optimized to avoid the load of data ingestion.

4. Security:

At every step, data has to be verified and go through the security standards to maintain the security. The organization needs to work on setting up a unique security standard to achieve a secure environment.

5. Costing parameters:

Data ingestion can be expensive. Several factors make it so. Maintaining the different types of data sources, handling the team, and depending on the decision that the company takes these factors can be a reason for costing parameters.

6. Manual Data Ingestion:

The process of data ingestion should be automated. When it comes to a large amount of data ingestion, manual data ingestion is not helpful. Rather, it has a lot of errors and extra work. Manual data ingestion becomes hectic and it is not an option as far as a huge amount of data is concerned.

Parameters to Evaluate the Tools for Data Ingestion:

There are numerous ETL tools available in the market. The main question is how to evaluate the best one? Based on the following parameters, organizations can pick suitable ETL tools as per their requirements.

1.  Security:

When it comes to data ingestion tools, security is the key factor. The tool should provide the latest security standards as the data is confidential.

2. Ease of use:

ETL tools should be easy to handle, they should not contain any sort of complexity. It can be the drag and drop functionality to avoid unnecessary errors and issues. In addition, it must allow the user to write customized complex SQL queries for transformation.

3. Pricing

Pricing is one of the major concerns in evaluating the data ingestion tools. Considering the overall factors and aspects, organizations should take prior steps as per their convenience.

4. Ability to transform the data:

Data is transferred from multiple data sources, and it may be in different formats, while the target location is expecting the company’s standard format. It should transform the data as per the requirement. It should have transformation features, which allows the user to write its customized transformation.

5. Data quality and Data leak:

As the data is fetched from different sources, the quality of the data should be maintained and there should not be a loss of data. The tool should take care of mapping the schema.


If you’re facing the challenges mentioned in the article, Snowflake is the ideal solution for you. With Snowflake’s convenient data loading and other capabilities, data ingestion can be a smooth and almost effortless process. Let us know which of the above parameters are of priority to you and we can take it from there.

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