Tools - Data Visualization, Data Mining & Maching Learning
So What is Data Visualization
Data Visualization is the process of slicing, dicing and visualizing data manually with the objective of identifying patterns, trends and characteristics in one’s data set. Data Visualization is an integral part of performance analysis regularly used to identify patterns within the business or infrastructure workload data for purposes of triage or diagnostics. Data Visualization tools are also used to visualize and analyze data as a first step before feeding them into modeling tools for purposes of modeling & forecasting. Data Mining and Machine Learning at concepts that we will be adding to over a period of time.
Provided below is a list of frequently used tools for purposes of Data Visualization. At this point this page includes just links to the various tool vendors or websites. Over a period of time we intend to introduce a summary of different tools, tool reviews including a short description of their strengths and weaknesses to help readers better grasp positioning of the relevant tools and frameworks within the enterprise.
|Vendor||Area Of Focus||Cost||Link|
|Elasticsearch-Logstash-Kibana (ELK)||Data Visualization||Free||Link|
|Zabbix & ELK In A Box (ELK)||Data Visualization||Free||Link|
|R Project||Data Visualization + Analytical + Statistical Modelling||Commercial||Link|
|Statistica||Data Visualization + Statistical Modelling||Commercial||Link|
Trevor Warren is passionate about challenging the status-quo and finding reasons to innovate. Over the past 16 years he has been delivering complex systems, has worked with very large clients across the world and constantly is looking for opportunities to bring about change. Trevor constantly strives to combine his passion for delivering outcomes with his ability to build long lasting professional relationships. You can learn more about the work he does at LinkedIn. You can download a copy of his CV at VisualCV. Visit the Github page for details of the projects he’s been hacking with.