Are you planning to integrate embedded analytics into your business application? You have made the right decision. Embedding analytics directly into your software, rather than using a third-party, separated access application, gives you a wealth of benefits. For example, it helps you to get maximum value from data, brings analytics deeper into standard workflows, and significant competitive advantage. Your software has in-built capabilities others don't.

Whether they know it or not, every company has become a data company. Data is no longer just a transactional byproduct, but a transformative enabler of business decision-making. In just a few years, modern data analytics has gone from being a science project to becoming the backbone of business operations to generate insights, fuel innovation, improve customer satisfaction, and drive revenue growth. But none of that can happen if data applications and pipelines aren’t running well.

BigQuery's Remote Functions (in preview) make it possible to apply custom cloud functions to your warehouse without moving data or managing compute. This flexibility unlocks many use cases including data enrichment. In this post we demonstrate a pattern for combining BigQuery with the Google Maps API to add drive times to datasets containing origin and destination locations. This enrichment pattern is easily adapted for address geocoding or adding Google Map's place descriptions to locations.

Today we are announcing the Preview of BigQuery Remote Functions. Remote Functions are user-defined functions (UDF) that let you extend BigQuery SQL with your own custom code, written and hosted in Cloud Functions, Google Cloud’s scalable pay-as-you-go functions as a service. A remote UDF accepts columns from BigQuery as input, performs actions on that input using a Cloud Function, and returns the result of those actions as a value in the query result.

Drag and drop analytics are more interactive and user-friendly compared to traditional, high code business intelligence (BI) solutions. They allow users without programming experience to easily explore the data and don't require coding knowledge, with a drag and drop user interface to conveniently enhance functionality of any dashboard report. In this post, you will find the importance of drag and drop analytics for more seamless reporting and user experiences when analyzing business-critical data.

Tuning Hive on Tez queries can never be done in a one-size-fits-all approach. The performance on queries depends on the size of the data, file types, query design, and query patterns. During performance testing, evaluate and validate configuration parameters and any SQL modifications.

Hitachi Vantara recently commissioned Forrester Consulting to conduct a Total Economic Impact (TEI) study to examine the value that customers could achieve using cloud and application modernization services from Hitachi Vantara. To better understand the benefits, costs, and risks associated with this investment, Forrester interviewed four decision-makers at companies with experience using cloud and app modernization services from Hitachi Vantara.

The idea of running compute and storing data in the cloud is no longer a novel concept. With the evolution of 5G and Internet of Things (IoT), this brings along the next evolution of edge storage demands. Today, around 10% of enterprise-generated data is created and processed outside a traditional centralized data center or cloud. By 2025, Gartner predicts this figure will reach 75%.