David Menninger's Analyst Perspectives

The amount of data flowing into organizations is growing exponentially, creating a need to process more data more quickly than ever before. Our Data Preparation Benchmark Research shows that accessing and preparing data continues to be the most time-consuming part of making data available for analysis. This can potentially slow down the organizational functions which depend on the analysis results. Trying to get ahead of the backlog with incremental improvements to existing approaches and traditional technologies alone can be frustrating.

Data integration or data preparation jobs take time to execute and generally run overnight – or even less frequently – making it difficult, or impossible, to analyze data from the same day’s operations. In an ideal world, the data in the analytical system would match the data in the operational system. Data would flow directly from one to the other without any need for transformation or modification.

A direct flow of data from operational systems can be accomplished if the process of optimizing the analytical system is performed behind the scenes. We assert that by 2022, the distinction between data preparation and integration technologies will blur, similar to the diminishing distinction between self-service analytics and data preparation, enabling better access to and use of data.

Incorta is a data and analytics platform that streamlines data preparation and integration for faster analysis. Its Direct Data Mapping technology automatically loads and analyzes incoming data in real time to provide operational analytics. Direct Data Mapping is Incorta’s data extraction layer, which allows you to extract a data table from the source system as a full or incremental load. The DDM engine automatically analyzes the incoming data, eliminating the need for most data modeling or optimization, which reduces implementation time. It supports over 200 data sources today, including a variety of cloud and on-premises business applications, databases, technologies and custom sources.

Incorta offers an analytics platform – now released in Incorta 5 – that can analyze large and complex business data sets in real time. The software makes it easy to connect to and ingest data from databases, data warehouses, cloud applications, data streams and data lakes. It also works with third-party analytical tools such as Microsoft Power BI, Tableau, MicroStrategy and Microsoft Excel.

In addition to dashboards and visualizations, Incorta can train and apply machine learning models. It can be installed in the cloud or on premises, and its flexible data controls allow access to be broken down by business groups and departments with inherited application security. The platform can run as a complete, standalone data and analytics platform, or as a component within a larger analytics and business intelligence technology portfolio. Incorta Cloud allows line-of-business users to spin up their own data analytics infrastructure without the help of IT, thus democratizing access to real-time, integrated data for analytics across the organization.

Incorta recently announced Incorta 5, introducing a series of new capabilities including access to new data sources, a redesigned data analyzer, a representational-state transfer application programming interface, data science notebook integration and a new, in-memory standard query language engine to enhance performance.

Incorta makes cloud data lakes continuously available for analytics. It can integrate with Azure data lake, Hadoop distributed file system data lake and Amazon S3 cloud-storage technologies. The software enables organizations to provide ready access to data that is currently stored in cloud data lakes, and bring new data into the cloud data lake storage as open source file format (Parquet).

Incorta can also automate accessing, loading and preparing data from multiple source systems in real time, allowing data engineers, data scientists, data analysts and business leaders to make more accurate, timely and transparent decisions with faster access to richer data sets. Incorta’s approach to data lakes focuses on the consumption of data rather than the approach of many data lake vendors that focus on the storage of data. Organizations looking to speed up the data preparation and integration processes should consider Incorta when evaluating vendors.

Regards,

David Menninger