10 JavaScript Data Table Libraries That You Should Know In 2021 - Solace Infotech Pvt Ltd

Javascript is a deciphered dynamic and untyped programming language, which establishes an interactive and phenomenal environment inside internet browsers on the internet. These days, Javascript components have become an intuitive string between customer and end user. These javascript data tables contain massive measures of information that you can handle with the help of libraries to allow additional assistance.

Data table library empowers the manipulation of HTML tables with big data set and also provides extended features like custom sorts, complex conditional styles, advanced searches, pagination, custom filters and line editing for your table. For web app development, it becomes easy for web app development to be an important and easy pursuit for the Javascript UI library and framework. It is beneficial for web developers to use these libraries and frameworks for easily building a clean, easy, consistent and attractive user interface.

Here we will discuss some of the most used JS data table libraries/grid and resource that developers may find useful and they could easily add grid functionality to tables, various functions like custom sorting, paging and advanced filtering on a huge data set.

10 Best JavaScript Data table libraries of 2021-

There are various factors that should be considered while choosing the most ideal Javascript Data table library. Some of these are as follows-

• Creating components inventory
• Shortlisting comprehensive and relevant components
• Looking for ready-made components according to business needs
• Looking for similar functionality and thereafter choosing the one out of them.

1. Fancygrid-
It is a javascript table library loaded with chart integration and server communication. This library works well with Angular 1 and 2, jQuery, VueJs and Web Components.ule. Fancygrid includes more than 25 features like sorting, paging, filtering, validation, touch support, REStful and so on. It is a plugin-free table library without any dependency and includes ample elegant API, samples, professional support, detailed documentation for convenience. One of the major drawbacks of this library is- it does not have mobile support.

2. Datatables-
Datatables is a plugin used to provide extra functionality for your tables like filtering, sorting, pagination and custom theming. It offers detailed documentation so you can handle look, feel, and work of your table. Wide range of features and customization makes it lovable among developers community. Another aspect of Datatable is that it offers a premium support via their forum that you get access to by purchasing one of their licenses. It offers some notable features like- column sorting, searching a string, individual column filtering, AJAX, export buttons, custom filtering, pagination, server-side processing, column reorder, and responsive extension.

3. Anygrids-
You can quickly create interactive tables from Javascript arrays, JSON formatted data, AJAX data sources with this vanilla library. One can include library in your project and just keep working on, without any adjustments. It allows you to filter, sort and group your data, use expanding table rows with custom data render, custom sparklines, use packaged themes, column calculation and pagination. New features are released consistently each month to make the customization process easier.

Know more at- https://solaceinfotech.com/blog/10-javascript-data-table-libraries-that-you-should-know-in-2021/

#javascript #libraries #technology #tech

What is GEEK

Buddha Community

Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

10 JavaScript Data Table Libraries That You Should Know In 2021 - Solace Infotech Pvt Ltd

Javascript is a deciphered dynamic and untyped programming language, which establishes an interactive and phenomenal environment inside internet browsers on the internet. These days, Javascript components have become an intuitive string between customer and end user. These javascript data tables contain massive measures of information that you can handle with the help of libraries to allow additional assistance.

Data table library empowers the manipulation of HTML tables with big data set and also provides extended features like custom sorts, complex conditional styles, advanced searches, pagination, custom filters and line editing for your table. For web app development, it becomes easy for web app development to be an important and easy pursuit for the Javascript UI library and framework. It is beneficial for web developers to use these libraries and frameworks for easily building a clean, easy, consistent and attractive user interface.

Here we will discuss some of the most used JS data table libraries/grid and resource that developers may find useful and they could easily add grid functionality to tables, various functions like custom sorting, paging and advanced filtering on a huge data set.

10 Best JavaScript Data table libraries of 2021-

There are various factors that should be considered while choosing the most ideal Javascript Data table library. Some of these are as follows-

• Creating components inventory
• Shortlisting comprehensive and relevant components
• Looking for ready-made components according to business needs
• Looking for similar functionality and thereafter choosing the one out of them.

1. Fancygrid-
It is a javascript table library loaded with chart integration and server communication. This library works well with Angular 1 and 2, jQuery, VueJs and Web Components.ule. Fancygrid includes more than 25 features like sorting, paging, filtering, validation, touch support, REStful and so on. It is a plugin-free table library without any dependency and includes ample elegant API, samples, professional support, detailed documentation for convenience. One of the major drawbacks of this library is- it does not have mobile support.

2. Datatables-
Datatables is a plugin used to provide extra functionality for your tables like filtering, sorting, pagination and custom theming. It offers detailed documentation so you can handle look, feel, and work of your table. Wide range of features and customization makes it lovable among developers community. Another aspect of Datatable is that it offers a premium support via their forum that you get access to by purchasing one of their licenses. It offers some notable features like- column sorting, searching a string, individual column filtering, AJAX, export buttons, custom filtering, pagination, server-side processing, column reorder, and responsive extension.

3. Anygrids-
You can quickly create interactive tables from Javascript arrays, JSON formatted data, AJAX data sources with this vanilla library. One can include library in your project and just keep working on, without any adjustments. It allows you to filter, sort and group your data, use expanding table rows with custom data render, custom sparklines, use packaged themes, column calculation and pagination. New features are released consistently each month to make the customization process easier.

Know more at- https://solaceinfotech.com/blog/10-javascript-data-table-libraries-that-you-should-know-in-2021/

#javascript #libraries #technology #tech

Getting Started With Data Lakes

Frameworks for Efficient Enterprise Analytics

The opportunities big data offers also come with very real challenges that many organizations are facing today. Often, it’s finding the most cost-effective, scalable way to store and process boundless volumes of data in multiple formats that come from a growing number of sources. Then organizations need the analytical capabilities and flexibility to turn this data into insights that can meet their specific business objectives.

This Refcard dives into how a data lake helps tackle these challenges at both ends — from its enhanced architecture that’s designed for efficient data ingestion, storage, and management to its advanced analytics functionality and performance flexibility. You’ll also explore key benefits and common use cases.

Introduction

As technology continues to evolve with new data sources, such as IoT sensors and social media churning out large volumes of data, there has never been a better time to discuss the possibilities and challenges of managing such data for varying analytical insights. In this Refcard, we dig deep into how data lakes solve the problem of storing and processing enormous amounts of data. While doing so, we also explore the benefits of data lakes, their use cases, and how they differ from data warehouses (DWHs).

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This is a preview of the Getting Started With Data Lakes Refcard. To read the entire Refcard, please download the PDF from the link above.

#big data #data analytics #data analysis #business analytics #data warehouse #data storage #data lake #data lake architecture #data lake governance #data lake management

Top 10 Big Data Tools for 2021!

In today’s tech world, data is everything. As the focus on data grows, it keeps multiplying by leaps and bounds each day. If earlier mounds of data were talked about in kilobytes and megabytes, today terabytes have become the base unit for organizational data. This coming in of big data has transformed paradigms of data storage, processing, and analytics.

Instead of only gathering and storing information that can offer crucial insights to meet short-term goals, an increasing number of enterprises are storing much larger amounts of data gathered from multiple resources across business processes. However, all this data is meaningless on its own. It can add value only when it is processed and analyzed the right way to draw point insights that can improve decision-making.

Processing and analyzing big data is not an easy task. If not handled correctly, big data can turn into an obstacle rather than an effective solution for businesses. Effective handling of big data management  requires to use of tools that can steer you toward tangible, substantial results. For that, you need a set of great big data tools that will not only solve this problem but also help you in producing substantial results.

Data storage tools, warehouses, and data lakes all play a crucial role in helping companies store and sort vast amounts of information. However, the true power of big data lies in its analytics. There are a host of big data tools in the market today to aid a business’ journey from gathering data to storing, processing, analyzing, and reporting it. Let’s take a closer look at some of the top big data tools that can help you inch closer to your goal of establishing data-driven decision-making and workflow processes.

Apache Hadoop

Apache Spark

Flink

Apache Storm

Apache Cassandra

…

#big data #big data tools #big data management #big data tool #top 10 big data tools for 2021! #top-big-data-tool

Introduction to Data Libraries for Small Data Science Teams

At smaller companies access to and control of data is one of the biggest challenges faced by data analysts and data scientists. The same is true at larger companies when an analytics team is forced to navigate bureaucracy, cybersecurity and over-taxed IT, rather than benefit from a team of data engineers dedicated to collecting and making good data available.

Creative, persistent analysts find ways to get access to at least some of this data. Through a combination of daily processes to save email attachments, run database queries, and copy and paste from internal web pages one might build up a mighty collection of data sets on a personal computer or in a team shared drive or even a database.

But this solution does not scale well, and is rarely documented and understood by others who could take it over if a particular analyst moves on to a different role or company. In addition, it is a nightmare to maintain. One may spend a significant part of each day executing these processes and troubleshooting failures; there may be little time to actually use this data!

I lived this for years at different companies. We found ways to be effective but data management took up way too much of our time and energy. Often, we did not have the data we needed to answer a question. I continued to learn from the ingenuity of others and my own trial and error, which led me to the theoretical framework that I will present in this blog series: building a self-managed data library.

A data library is _not _a data warehouse, data lake, or any other formal BI architecture. It does not require any particular technology or skill set (coding will not be required but it will greatly increase the speed at which you can build and the degree of automation possible). So what is a data library and how can a small data analytics team use it to overcome the challenges I’ve described?

#big data #cloud & devops #data libraries #small data science teams #introduction to data libraries for small data science teams #data science