Like conventional analytics and business intelligence solutions, big data mining and analytics helps uncover hidden patterns, unknown correlations, and other useful business information. However, big data tools can analyse huge volumes of diverse information assets more effectively. These tools overcome challenges of capturing, managing, and processing data faced by traditional big data tools. Additionally, they help in efficient data management, timeliness, and cost-effective business solutions.
Currently, businesses are implementing big data systems and solutions like MapReduce, Spark, Hadoop, NoSQL etc for supporting strategic business decisions. Features of popular big data management tools have been explained here.
This SQL-on-Hadoop tool derives real-time key insights benefiting businesses to aim for rapid development. Users can use standard SQL and tackle limitations posed by Oracle and MySQL. Compliant with SQL99 as well as ANSI SQL, this data management tool supports Java, .NET, Python, and AngularJS.
Able to manage heavy data loads, this tool provides instant updates and alerts to users. Geographical data in consonance with location relevance and content is accessible as well. High-quality data filtration tools make it an ideal choice for developing paid content search apps. Flexible API support such as NoSQL, and Node.js are an additional feature. It facilitates development of stable data reference architecture using sample codes under Samplestack.
Conquering the field of search engines, Google has explored several IT solutions for app development, and is a strong contender for developing big data technologies as well. Simple charts and hierarchical tree maps offer easy and quick data visualization. Users can sort, filter, and modify data along with connecting to a site’s database or download it directly.
This freeware offers multilingual support and enhances data security, offering a great product to developers.
Although, distinctive features cannot classify this tool entirely for report-generation or collection of AI routines, it helps in data indexing. Text-search methods offer flexible data indexing. Attuned with specific applications, even new developers can understand log files and create different solution packages appropriately. Data correlation with common servers is possible with Splunk big data management tool. In addition, it serves as a great tool for detecting cyber-attacks.
Making Data Management Easy with Big data technologies
Exponential growth of Big Data is challenging. Several data types are being created and likewise proliferating. In addition, speed of data creation puts additional pressure on the demand of quicker data analysis in order to derive real-time value.
However, several tools along with those mentioned above prove useful in taming big data. Innovative approaches of storing, processing, and analysing multistructured data helps in discovering valuable business insights every day.
Market leaders include LinkedIn, Amazon, and Facebook closely followed by start-ups in diverse sectors. From analysing social graphs and marketing campaigns to monitoring networks, detecting fraud, and risk modelling BIG Data has an answer to all.