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Understanding ETL Tools as a Data-Centric Organization

Smart Data Collective

The ETL process is defined as the movement of data from its source to destination storage (typically a Data Warehouse) for future use in reports and analyzes. The data is initially extracted from a vast array of sources before transforming and converting it to a specific format based on business requirements.

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How Data Management and Big Data Analytics Speed Up Business Growth

BizAcuity

Big Data technology in today’s world. Did you know that the big data and business analytics market is valued at $198.08 Or that the US economy loses up to $3 trillion per year due to poor data quality? quintillion bytes of data which means an average person generates over 1.5 Big Data Ecosystem.

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TIBCO JasperSoft for BI and Reporting

BizAcuity

Boris Evelson, principal analyst at Forrester Research pointed out that while Jaspersoft may not match the likes of Oracle, Microsoft, or IBM, feature for feature. JasperSoft is available at a fraction of the cost compared to its commercial counterparts who dominate the market. Data Security. JasperSoft for Big Data Analytics.

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How The Cloud Made ‘Data-Driven Culture’ Possible | Part 1

BizAcuity

Despite cost-cutting being the main reason why most companies shift to the cloud, that is not the only benefit they walk away with. Cloud washing is storing data on the cloud for use over the internet. While that allows easy access to users, and saves costs, the cloud is much more and beyond that. Hadoop was developed in 2006.

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Skills and Tools Every Data Engineer Needs to Tackle Big Data

Sisense

To do that, a data engineer needs to be skilled in a variety of platforms and languages. In our never-ending quest to make BI better, we took it upon ourselves to list the skills and tools every data engineer needs to tackle the ever-growing pile of Big Data that every company faces today. Data Warehousing.

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The Data Journey: From Raw Data to Insights

Sisense

Traditionally all this data was stored on-premises, in servers, using databases that many of us will be familiar with, such as SAP, Microsoft Excel , Oracle , Microsoft SQL Server , IBM DB2 , PostgreSQL , MySQL , Teradata. Sisense provides instant access to your cloud data warehouses. Connect tables.

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Acquisitions on the Horizon in BI and Data Analytics Industry?

Sisense

Operating “in-data” to enable the direct query of unstructured data lakes, providing a visualization layer on top of them. This is typically done on top of a high-performance database and, these days, on top of a cloud data warehouse. To see a BI vendor doubling down on in-data technology isn’t surprising.