Data Integration

It is possible to create scripts to scrub the data, and then load it into a data warehouse, or use traditional extraction, transformation, and loading tools to integrate data from different sources.
However, these methods are very time-intensive, expensive, and error-prone. Traditional methods require data scientists to spend an enormous amount of time cleansing data because the data at
the source and target may not use the same schemas, formats, or types.
And traditional data integration tools are usually batched, rather than real-time. These methods are also expensive because they require a robust infrastructure and skilled manpower.

Modern data integration tools use data pipelines and support a variety of integrations to replace outdated traditional methods of manually managing data sets, scrubbing them, and loading them into the individual data lake or data warehouse environments. Now, you can store, stream, and deliver the data you need, when you need it, from any cloud data warehouse — Amazon Redshift, Snowflake, Google Big Query, Azure, or a number of other options. You can define data types and destinations, enrich the data stream, and check for errors while the data is streaming. Then, you can get the real-time insights you need to make good business decisions.

Perhaps of equal importance is the security that a modern data integration solution can offer. Any time data is moved from one place to another, the security risk increases greatly. However, ARMS IT provides a well-designed modern enterprise data platforms makes security a first priority. For example, 100% SOC 2 Type II, ISO27001, HIPAA, and GDPR compliant, and our supported cloud service providers meet the strictest standards in the industry.