With millions of online transactions, and with billions of IoT (Internet of Things) sensors pour in information, it is critical to make sense of this data in real-time for the success of any Organization. Machine learning (ML) and artificial intelligence (AI) programs churn through vast data troves. Companies compile behavioral, financial, and medical information from consumers. And businesses like yours increasingly succeed or fail depending on how they handle this deluge of data
Effective data acquisition, integration, and interpretation have quickly become essential data management strategy tasks. For financial institutions, insurers, retailers, healthcare providers, and everyone else who deals with customers, partners, and regulators, a forward-looking data strategy is a board-level issue. An effective data & analytics strategy provides:
QuickInfer has the engineering expertise to help you capitalize on the high value data you are constantly collecting by connecting that data across departments, bolstering analysis, and building better reporting capabilities — all in real-time. With its in-built full-stack data management platform, this activity is made seamless for Organizations
Enterprise Information Management (EIM) technologies, processes and practices help you improve efficiency and enable faster business insights. Gartner says that by 2020,
75% of organizations that use Enterprise Information Management to align, link and leverage their data and analytics investments will report substantially improved business outcomes.
EIM provides end-to-end data lifecycle management, including data integration, data warehousing and analytics, reports and dashboards, data tool migration/upgrade, master data management, and data quality and lineage, along with the right tools to achieve each.QuickInfer’s data team can help you utilize EIM to:
Petabytes, zettabytes, and beyond. Big data continues to grow. How do you ensure you can mine big insights from your ever growing data? Big data refers to data sets whose size or type is beyond the ability of traditional relational databases to capture, manage, and process the data with low latency. Big data includes structured, semi-structured and unstructured data, from different sources, and in different sizes.
With an explosion of data from more sources than ever before, storing and managing these huge pools of information is a big challenge.And regardless of the size of your data cache, you must be able to extract the right metrics at the right time. Big data services enables users to make better and faster decisions using data that was previously inaccessible or unusable. QuickInfer’s team can help with data discovery, data quality, data visualization, and big data/social media analytics.
Cloud analytic solutions have arrived and are here to stay. Cloud analytics moves data processing and storage operations to a private or public cloud network. You’ll get all the benefits of the cloud – rapid spin-up, flexibility, scalability – and you only pay for what is used.
You have many disparate data sources, and it’s difficult to see all the moving parts if the data is housed in different locations. A cloud implementation consolidates your data so it’s more easily accessible. That ease of access can lead to more sharing and collaboration between employees as well. And, you’ll reduce operating costs when you don’t need to purchase additional hardware or software, or provide continuous support and ongoing upgrades.
QuickInfer’s cloud analytics product called BIRD includes solutions such as Data Lakes and DataHubs for ETL (Extract/Transform/Load), data warehouses, and on-demand business intelligence.
Contact us to see what architecture is right for you.
Artificial Intelligence (AI) allows machines to sense, comprehend, learn, and act. AI can provide recommendations on your streaming platforms, systems designed to intelligently trade stocks, or maneuver an autonomous vehicle.
Machine Learning (ML) takes AI to another level by giving machines access to data and letting them learn for themselves. For example, ML apps can read text and determine whether the writer is making a complaint or offering a recommendation, or listen to music and decide whether it is likely to make someone happy or sad.
Do you need better data security like risk identification or early detection? What about real time analytics to find fraudulent transactions or provide dynamic pricing? Can data visualizations and dashboards identify irregularities in data or help support predictive analytics? AI and ML can help you turn data into decisions at any scale, anywhere, and QuickInfer can help you build, deploy, and scale AI and ML applications with expertise in prediction models, recommender engines, bots, and cognitive services.