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Data Analytics
Data Analytics

Data is unlike any other asset your organization owns. It never wears out, it never depletes, and can be used repeatedly at zero additional marginal cost. The value in data is not having it, it's in how you use it. SourceOn IT drives this value from your data with solutions that automate data transformation and machine learning (AutoML) processes and tasks.

Without needing to code, SourceOn IT efficiently and accurately prepare data for Explainable AI that displays the fine details of a model’s configuration so you can better understand how predictions are made. You can be confident your people are making decisions based on trusted, accurate, and interpretable data.

Data analytics is important because it helps businesses optimize their performances. Implementing it into the business model means companies can help reduce costs by identifying more efficient ways of doing business and by storing large amounts of data. Data analytics can do much more than point out bottlenecks in production.

 

"Each of the three data science disciplines has its own excellence. Statisticians bring rigor, ML engineers bring performance, and analysts bring speed"

Descriptive analytics: Data that provides information about what has happened in your company. It's like an overview of the Company's performance. Just like a  monthly sales report, purchases, marketing campaign, etc. It's gathering the raw data and summarizing it so that it is easily intercepted. For most businesses, descriptive analytics form the core of their everyday reporting. This includes simpler reports such as inventory, workflow, warehousing, and sales, which can be aggregated easily and provide a clear picture of a company’s operations.

Predictive analytics: Data that provides information about what will happen in your company. Predictive analytics is an advanced analytics technique to unravel and predict the future of the company. It helps you transform the way you see the statistics of your company with the help of more complex machine learning and AI processes and algorithms, predictive analytics help you determine what will happen—how well a product will sell, who is likely to buy it, which marketing to use for the greatest impact.

Prescriptive analyticsData that provides information on not just what will happen in your company, but how it could happen better if you did x, y, or z. Beyond providing information, prescriptive analytics goes even one step further to recommend actions you should take to optimize a process, campaign, or service to the highest degree. It also provides organizations with recommendations around optimal actions to achieve business objectives like customer satisfaction, profits and cost savings. Prescriptive analytics solutions use optimization technology to solve complex decisions with millions of decision variables, constraints and tradeoffs. Organizations across industries use prescriptive analytics for a range of use cases spanning strategic planning, operational and tactical activities.

Why Is Analytics Important?

Imagine a steady stream of insights to fuel intelligent technologies; 360-degree customer views to boost relevance and revenue; or faster, smarter decisions to accelerate innovation. Analytics can do that for you. With data continuing to grow in size, scope, and complexity, organizations are hungry for innovative strategies, services, and technologies to unlock the value of their data analytics potential.

Data analytics is a broad term that encompasses many diverse types of data analysis. Any type of information can be subjected to data analytics techniques to get insight that can be used to improve things. For example, manufacturing companies often record the runtime, downtime, and work queue for various machines and then analyze the data to better plan the workloads so the machines operate closer to peak capacity. We work with our clients to support their missions by developing end-to-end solutions.

Data analytics applies to all industries including Financial Services and Insurance, Manufacturing, Energy, Transportation, Travel and Logistics, Healthcare, and others. Data analytics can help predict and handle disruptions, optimize routes, deliver proactive customer service, make smart cross-sell offers, predict impending equipment failure, manage inventory in real time, optimize pricing, and prevent fraud

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