How to Intelligently Apply Data Integration and Visual Analytics Tools

How to Intelligently Apply Data Integration and Visual Analytics Tools

How to Intelligently Apply Data Integration and Visual Analytics Tools

Data integration requires merging date from different sources, stored using technologies. Companies build a “data warehouse where aggregated data can be stored and retrieved. This is particularly useful for researchers looking to big data to aid in their investigation and corporations usually during the merging with other companies.

According to ,Dataintegration,  integration of data can be performed using several organizational levels such as:

Users can access all systems of different sources or interface of web pages but without viewing consolidated data.

Integration of Data Based On Different Applications

This organizational level requires particular applications to integrate data.

This data integration organizational level transfers the integration of data from particular applications to a new layer of middleware.

This provides a unified view of data that can be accessed across the whole enterprise. One of the advantages of uniform data access or virtual integration is the nearly zero latency of data updates from the source to a unified view. A user can access customer information transparently obtained from the system.

Read Also:
BI software trends in 2017: The role of big data analytics

This means a new system is created to store and manage data from the source systems. The most common example is the data warehouse. However, physical integration of data requires a system of its own to handle huge amount of data.

Companies, marketers, data scientists and researchers can all benefit from this never-ending stream of information available to them by putting them into visualization tools to be able to study and analyze aggregated data.

Data Visualization is the presentation of data by using graphs and charts. It enables researchers to visually grasp complicated concepts or identifying new trends and patterns.

Here are some of data visualization tools for data analysis

MicroStrategy Analytics Desktop is user-friendly software for visual data analytics. This allows you to connect any database you need, import documents like excel and spreadsheets, files and other online sources. Through these you can gain insights from visualization of data.

Domo boosts an intelligent UI and is specifically designed to allow users to create dashboards, and particularly suited to users who are interested in visualizing in cloud-based apps. Domo can take input from databases, spreadsheets, and social media platforms viewable on handheld devices like mobile phone and tablets.

Read Also:
Bridge the CxO Gap with a Data-Driven Approach

Tableau offers a variety of tools that include an online and server versions. Tableau can connect to live-data for real time visualizations or warehoused data.

Qlikview has the ability to quickly visualize data with a custom-data visualization dashboard that allows real-time visualizations.

These are just some of the visual analytics tools available for researchers to be able to analyze and study data taken from different sources and data warehouses.


Read Also:
Big Data and business analytics a $200 billion industry
Predictive Analytics Innovation summit San Diego
22 Feb

$200 off with code DATA200

Read Also:
How healthcare can play safe in the data lake
Read Also:
How Nonprofits Can Benefit From Big Data
Read Also:
Data Privacy, Security, and the Connected Car
Read Also:
Business Intelligence Analytics is the Future of SaaS -Big Data Analytics News

Leave a Reply

Your email address will not be published. Required fields are marked *