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.

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Many organizations are turning to Snowflake to store their enterprise data, as the company has expanded its ecosystem of data science and machine learning initiatives. Snowflake offers many connectors and drivers for various frameworks to get data out of their cloud warehouse. For machine learning workloads, the most attractive of these options is the Snowflake Connector for Python.

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.

Reporting is more important than ever. Long gone are the days of filling out excel sheets at year end and filing them away into oblivion, never to be seen again. The reports you file now, are not only more transparent than ever, but they have much more impact in the future and trends of your business than ever before.

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%.