What is a Data Annotation tool?

A data annotation tool is a cloud-based, on-premise OR containerized software solution. You can use it to annotate any type of data/training for machine learning and enable machines to learn human intelligence. Although there exist several Data Annotation tools in the market, some organizations build their own.

To make an informed choice concerning a Data Annotation tool, you must know its key features, along with what kind of annotation is required for a particular data, like polygon, bounding box, polyline or point. It is because the process also involves data preparing, quality annotating, training, testing, and validating for a particular model.

To understand what it’s looking for: A computer vision system uses annotated training data to help it analyze, recognize and identify the pattern, objects and distances for particular data.

Some essential features of an Annotation tool include,

• Dataset Management
• Annotation method
• Data quality control
• Workforce management
• Security

The common type of annotation capabilities provided by data annotation tools includes building and managing ontologies and guidelines.

• Label maps (task)
• Classes
• Attributes
• Specific annotation type

Data Analytics

If you want to get ahead of the pack in commerce, you’ll need to make informed decisions and capitalize on opportunities and inefficiencies around your business. The digital age has made it so much easier to do that with the introduction of data analytics tools. Analyzing data has become the norm in 2020 and beyond, so much so that it’s diffused enough to get to free and open-source data analytics tools for any level.

8 Open-Source Tools To Start Your NLP Journey

Teaching machines to understand human context can be a daunting task. With the current evolving landscape, Natural Language Processing (NLP) has turned out to be an extraordinary breakthrough with its advancements in semantic and linguistic knowledge. NLP is vastly leveraged by businesses to build customised chatbots and voice assistants using its optical character and speed recognition techniques along with text simplification.

To address the current requirements of NLP, there are many open-source NLP tools, which are free and flexible enough for developers to customise it according to their needs. Not only these tools will help businesses analyse the required information from the unstructured text but also help in dealing with text analysis problems like classification, word ambiguity, sentiment analysis etc.

15 Best Open Source Data Visualization Tools 2021

Data visualization tools are used to represent information with graphs, charts, tables, maps, and other detailed visuals.

They usually combine data presentation and analysis to help professionals in making more informed decisions in data-driven fields (such as engineering, data science, and business analysis).

Choosing the right data visualization tool will help you to reduce data errors and save enormous time and resources in your workflow. And, choosing open-source options would offer you considerable freedom for customizing the tool in question to suit your particular needs.

8 Best Open-Source Tools for Data Mining

One of the popular terms in machine learning techniques is data mining. It is the process of extracting hidden or previously unknown and potentially useful information from the large sets of data. The outcome can be for analysing and achieving meaningful insights for the development of an organisation.  

Top 7 Open-Source Master Data Management Tools – 2021

In today’s world, businesses can accumulate an enormous amount of data. In 2021 it can be used cross-functionally across different departments. Hence it can lead to a lot of data anomalies, redundancy, complexity, fragmentation, etc.

For this reason, it is easy to get confused with your data. Answering the core questions such as, “What is this particular data used for?” or “Who are the main clients?” becomes a problem.

To answer the above questions we have Master Data. The MD will remain unaltered, irrespective of how many times the data is processed across multiple channels. And Master Data Management is how the information or data is managed and categorized for future use.

Master Data Management Tools synchronized with different teams. Sales, Marketing, IT, and Operations all these can benefit by having a master data.

9 Great DataOps Tools For Your Team

Now that organizations are dealing with big data on a day-to-day basis to generate useful insights, we require more efficient software/data development lifecycles.

The era of big data calls for some powerful data operation tools which can automate processes and reduce the cycle time of the data analytics for enormous datasets. For this purpose, the concept of DataOps is what works as the solution. It is a process-oriented methodology that monitors and controls the data analytics pipeline by using Statistical Process Controls.