Data Science and Machine Learning

What is Data Science and Machine Learning?

Data science and machine learning

Modern analytics is a combination of analytical functions and data science. Machine learning requires large amounts of raw transactional data, exactly the type of data Incorta provides with impressive speed.

Integrated data analysis and data science

Incorta makes data science 'just work' by integrating big data processing and machine learning into the analytical data pipeline.

• Incorta groups a preconfigured Spark cluster to perform data enrichment tasks, including machine learning, and to parallelize operations such as data loading and reduction.
• Complex operations can be easily programmed with integrated Python, Scala, R, and SQL notebooks.
• An integrated machine learning library makes it easy to set up time series predictions, detect discrepant values, sort, and many other models.
• Integrated task scheduling makes it easier to orchestrate model retraining, predictions, and monitoring.
• Easy-to-use tools for data analysis and visualization provide data validation, insights discovery, and discovery presentation.

By combining data management, analytics, and data science into a single platform, Incorta means more data science with less data contention.

Believe your summary data to details

Original full-fidelity data means the freedom to ask any question, traverse drilling paths and hierarchies, perform root cause analysis, explore unlimited perspectives, and go from first-line KPIs to transactional support records in the blink of an eye.

From strategic decisions to root cause analysis, they all start with the same dataset.

Unlike a data warehouse, Incorta keeps all your data in its original form, providing you with a single source of truth for strategic and operational decision making, data science and machine learning, and other computational workloads.

This means that with Incorta, you can analyze large amounts of raw business data in real time, without transformation, while also being able to delve into the details, ask any questions, and even train machine learning models.

System requirements:

CPU: 1.8 GHz dual core processor

RAM: 2 GB

HDD / SSD: 50 GB of free space on the main drive

Operating system: Microsoft Windows 10, Microsoft Windows 8 32-bit, Microsoft Windows 7 32-bit and Microsoft Windows Vista 32-bit

Resolution: 1024×768

Supported operating systems

Mac OS X 10.5 x (Leopard), Mac OS X 10.6 (Snow Leopard), Mac OS X 10.7 (Lion), Mac OS X 10.7 (Mountain Lion), OS X 10.9 (Mavericks) and Mac OS X 10.10 (Yosemite)

Hardware requirements

Memory - 1 GB of RAM and more

Free disk space - 50 MB

System type - 32-bit and 64-bit OS