Microsoft Power BI
Tableau
Looker
Sisense
Qlik
QlikSense
Domo
Metabase
Apache ORC
Impala
SQream
Apache Kudu
Apache Parquet
Amazon EMR
RJ Metrics
Apache Arrow
Microsoft Power BI Apache ORCBased on our record, Microsoft Power BI should be more popular than Apache ORC. It has been mentiond 17 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Microsoft Fabric is currently in preview and provides data integration, engineering, data warehousing, data science, real-time analytics, applied observability, and business intelligence under a single architecture by integrating services such as Azure Data Factory, Azure Synapse Analytics, Data Activator, and Power BI. In addition, it comes with a SaaS, multi-cloud data lake called "OneLake" that is built-in and... Source: about 1 year ago
I'd suggest spending some time learning the material before you invest thousands in tuition only to find that you don't like it or aren't good at it. Download Tableau Public or Power BI and force yourself to use them for a few months. That's how I taught myself R. Source: about 1 year ago
Discover why business analytics is crucial for your business and how to utilise data analytics and PowerBI to make informed and data-backed decisions! Source: about 1 year ago
Power BI is popular... But for table reports with Excel/PDF export you can use Pebble Reports. Source: over 1 year ago
Yes, MySQL can do the job. You can use Airforms to do data entry. No need to learn MySQL syntax. You will also need a reporting tool, such as Power BI. Source: over 1 year ago
The information can be stored in a database or as files, serialized in a standard format and with a schema agreed with your Data Engineering team. Depending on your information and requirements, it can be as simple as CSV, XML or JSON, or Big Data formats such as Parquet, Avro, ORC, Arrow, or message serialization formats like Protocol Buffers, FlatBuffers, MessagePack, Thrift, or Cap'n Proto. - Source: dev.to / over 1 year ago
Data formatting is another place to make gains. When dealing with huge amounts of data, finding the data you need can take up a significant amount of your compute time. Apache Parquet and Apache ORC are columnar data formats optimized for analytics that pre-aggregate metadata about columns. If your EMR queries column intensive data like sum, max, or count, you can see significant speed improvements by reformatting... - Source: dev.to / over 2 years ago
The following stack captures layers of software components that make up Hudi, with each layer depending on and drawing strength from the layer below. Typically, data lake users write data out once using an open file format like Apache Parquet/ORC stored on top of extremely scalable cloud storage or distributed file systems. Hudi provides a self-managing data plane to ingest, transform and manage this data, in a... - Source: dev.to / almost 3 years ago
Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.
Impala - Impala is a modern, open source, distributed SQL query engine for Apache Hadoop.
Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
SQream - SQream empowers organizations to analyze the full scope of their Massive Data, from terabytes to petabytes, to achieve critical insights which were previously unattainable.
Sisense - The BI & Dashboard Software to handle multiple, large data sets.
Apache Kudu - Apache Kudu is Hadoop's storage layer to enable fast analytics on fast data.
