Embedded Analytics: The Solution to Controlling Large Data Sources

By Logi Analytics
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Pain Point:  I need my analytics to pull in data from multiple large data sources. What is my best option?

Solution: An embedded analytics solution allows for a seamless analytics experience using your current data and server infrastructure, including large data sources.

These solutions, such as Logi Composer, were designed to be able to scale with your business operations, whether you operate on-premise, in the cloud, or you use a hybrid infrastructure approach.

Being able to interact with data – and make business decisions in real-time – is an important component of analyzing big data in a streamlined manner. Data can be represented in streams that are baked into the web application, Query Engine, and data connectors inside of Logi Composer.

Logi Composer is designed so users can utilize smart data connectors and modern data stores comprising of search engines, streaming, and cloud data warehouses. This functionality allows for a complete customization of embedded analytics, so users don’t miss a step once the out-of-the-box features are implemented. With Logi, you can:

  • Apply filters, aggregations, or calculations at the source
  • Process thousands of concurrent user queries with exceptional speed and performance
  • Empower users with data from multiple sources for rich, in-depth data analysis
  • Embed and extend components with integration flexibility
  • Connect to streaming, search, big data, NoSQL, cloud, and document-based sources
  • Connect to traditional databases: relational, data warehouses, flat files

These features aren’t relevant without compatibility with other software that is commonly used in a business environment. For this reason, Logi works with SQL Server, Oracle, MySQL, PostgresSQL, Amazon, Redshift, Mongo DB, Hadoop, Snowflake, Apache Solr, Elasticsearch, SparkSQL, Impala, and more.

Connecting to large data sources allows teams to avoid heavy data modeling, with filters, aggregations, and calculations conducted directly at the source. A modern analytics platform also makes it so databases can take advantage of faster queries and optimized data storage.

Organizations branching out to launch data-driven projects are now discovering that every application, whether apparent or not, is now becoming an analytic application. Organizations looking to migrate from aging business intelligence platforms to embedded analytics benefit from a modern platform in the age of big data.

In today’s constantly changing times, a modern data project will likely encounter a time when data complexity and performance forces decision makers to re-evaluate their data architecture. As part of the plan, it’s important to think about both short-term and long-term goals, understanding the end user, what data will be delivered, and current infrastructure shortcomings.

Moving into the future, even more data will be created and collected in the workplace, so it’s important to find methods to take advantage of what’s important for your decision-making process. If you’d like to learn more, you can try out Logi Composer for yourself.

Originally published October 8, 2021

About the Author

Logi Analytics is the leader in embedded analytics. We help team put business intelligence at the core of their organizations and products.