Every organization needs a flexible and efficient way to handle its data! Through successful Analytics Process Automation (APA) and data-driven decision-making, we can optimize the critical business operations which generate maximum revenue for the organization and deliver the highest value for its customers.
In this article DATAFOREST will walk you through the steps of process automation, the adoption of APA category platforms, and which tools you should consider when implementing an APA strategy.
Now let's dive into it!
The Automation World: Business Analytics and Data Science
Analytics refers to all of the models, algorithms, data analysis, and insights generated through the use of mathematical and statistical methods, data mining, artificial intelligence and machine learning techniques in order to solve complex business problems.
Business analytics is a term used to describe the process of collecting, analyzing, and reporting data to help a company make better decisions. Business analytics can be used to improve any aspect of a business—from customer service to marketing and sales strategies, or even day-to-day operations like supply chain management.
Automated data management is key to successful data science. Without it, it’s a struggle to build systems that are fast, secure, and scalable enough to handle all of your data needs.
Process automation is the next step in the evolution of business analytics. With DATAFOREST tools and techniques automation can be applied to just about any process that needs streamlining and optimization.
How Important is Automated Data Management For Business Analytics?
In the past, it was common for an enterprise to employ a data warehouse and business intelligence software to analyze its data. This approach was both manually intensive and time-consuming. Companies are rapidly adopting automated approaches – using advanced algorithms and data-pipelines that can quickly acquire and process large amounts of data, find patterns and provide recommendations based on those patterns.
According to “QuantumBlack AI by McKinsey”, by 2025, smart workflows and seamless interactions among humans and machines will likely be as standard as the corporate balance sheet, and most employees will use data to optimize nearly every aspect of their work. Many successful businesses are realizing the power of analytic process automation now, and they need to ensure that these processes are sustainable, repeatable, secure, and scalable.
There are many ways to approach advanced business analytics. One of them is using analytic process automation, or APA.
What is Analytical Process Automation (APA) & How Does it Work?
Analytic process automation is a term that refers to a group of technologies used to streamline the data analysis process. The APA framework is a plug-and-play data science, AI, and ML solution to automate the process of transforming data into actionable insights. It's a way of applying the world's best business analytic and data-science practices to empower an entire organization.
The APA approach creates a workflow that represents the steps taken to get from raw data to an answer, which can be modeled using machine learning. This workflow is then executed repeatedly in response to changes in raw data or circumstances. This approach allows companies to improve their decision-making capabilities by increasing accuracy and reducing costs associated with manual data transformation and ingestion processes.
How to Empower an Entire Organization with Analytics Process Automation?
APA enables the entire corporate ecosystem of data scientists, business analysts, IT professionals, and other employees to collaborate in a manner that enables them to be more productive and efficient while maintaining the integrity of the data and processes.
The benefits of APA are far-reaching: it can help improve a businesses customer experience and increase sales, while also allowing more informed decisions about business operations. APA also improves security, as it reduces manual intervention and human error.
Businesses today are increasingly embracing APA to improve their decision-making capabilities by extracting valuable insights from vast amounts of data. Automation-based management is essential for corporations because it allows them better perform complex tasks related to analytics.
What Are The Steps for Process Automation?
Traditional business analytics platforms are great for simple data reporting, but to take a company's decision-making process to the next level, then a move into process automation is needed. Process automation is the practice of using software and hardware to automate repetitive tasks in order to save time and money.
There are four main steps of process automation: design, develop, deploy, and manage.
The design phase determines the needs of the project. This defines what data will be used and how it can be used to create insights. During this step, consideration is given to the tools which will be needed for development as well as the resources are available within the organization. Once the design step is completed, it’s time to move on to the development of an implementation plan.
The goal of this phase is to create a design for a system which will automate all of the tasks related to the project. This plan should include any integrations with other systems as well the collection, processing, and storage of the data. Once this step is completed, it’s time for deployment.
Deployment involves implementing the designed solution. This will include testing and debugging, as well as any training needed by the organization’s employees.
When there is a well-established culture of analytics and a good understanding of the processes which the organization needs to automate, it's time to enhance the business with APA category platforms.
What Are APA Category Platforms?
An APA category is a set of tools, software, or apps that enable businesses to perform complex data science and business analytics tasks. APA category platforms allow users with no-coding experience to access advanced analytics, AI, and ML capabilities through simple drag-and-drop interfaces.
No matter what a company's needs are, there is an APA platform that can help maximize the impact of data science efforts and manage business processes. These tools are designed to help automate entire analytic workflows - from product development to staffing decisions—and everything in between!
What Are The Best Tools And Solutions For Analytical Process Automation?
The best tools and solutions for analytical process automation are the ones which allow companies to make the most of their data. The more workflows which can be automated, the more time organisations will have to focus on other aspects of the business.
Successful businesses are all realizing the power of data APA, and they need to ensure that these processes are repeatable, secure, and scalable. This is where DATAFOREST comes into play: an agile team of engineers and data scientists who build products and solve problems.
DATAFOREST helps businesses succeed by tapping into the full potential of data to deliver more intelligent, faster decision-making across their organizations.
The following are DATAFOREST advanced data science solutions in the APA category:
Data Mining & Management
Data mining and management is the process of acquiring, preparing, ingesting and analyzing large amounts of data to identify patterns and make predictions. Data mining is a business analytics decision-making solution that will help you make better decisions for your business.
DATAFOREST offers a variety of solutions for data mining, ranging from simple web scraping to complex data warehouse solutions. The DATAFOREST team can help businesses acquire, store, and analyze data from a large range of sources, collect this information in a useful way and then present it in an easy-to-understand manner.
Email & Marketing Automation
Many companies use email and marketing automation to enhance lead-generation efforts. These tools allow businesses to find potential clients based on social media data and monitor public opinion, and product reviews. Also supported is the addition of chat/email bots to the lead pipelines, segmentation of clients for personalized promotions, tracking and autotuning of campaigns, and much more.
Data visualization is one of the most powerful tools in any business analyst's arsenal, allowing the visualisation of trends, outliers, patterns, and other insights which would be difficult or impossible to see otherwise. That ability can help make data-driven decisions quickly and efficiently, reducing analysis time
DATAFOREST is a complete business analytics decision-making solution that helps you visualize data in a way that makes it easy to understand. DATAFOREST will help with a whole range of tasks, starting from visualization design up to analytical apps to help make data-driven decisions.
Scripts & Utilities
Automation scripts: automate business processes and reduce human effort involved in continuous, routine tasks. Build custom automation rules, build custom workflows for repetitive computer tasks, generate and update Excel, PDFs, and Word documents, scrape and crawl websites.
Utilities: manage the data warehouse with ease by interacting with it via a graphical user interface. Connect to different databases, import and export data, create reports.
Get more out of the AI era with Data Forests Machine Learning services. Define and train your own decision-making algorithms, reduce costs and increase sales. The possibilities are endless!
Machine learning is used to solve real-world business problems. From email bots that analyze the intent of a lead and route them to the appropriate salesperson, to cross-sell and up-sell recommendations using the neural network, Machine Learning has become an integral part of many companies' data strategy.
DATAFOREST specialize in automating business processes. From enriching customer data with artificial intelligence tools that analyze customer behavior and predict the best time to communicate, to custom-built ERP systems that fit exactly with business needs and solve unique problems.
The DATAFOREST CRM and ERP solution is designed to meet the requirements of all types of businesses. From planning and forecasting to cultivating customer experience, the intelligent software suite helps to measure, manage and optimize processes for competitive advantage in today’s fast-moving marketplace.
Data Analysis & Testing
DATAFOREST is an ecosystem of quantitative business intelligence tools. It can be used to measure sales, demand, and inventories, and optimize the supply chain, on top of hundreds of other use cases.
The ability to recognize the opportunity and capitalize on it is the mark of a successful entrepreneur. By using APA solutions, they are able to remove obstacles that stand in the way of progress and have the power to continue making decisions that lead to success.
DATAFOREST is a leading provider of disruptive data science services, analytic process automation solutions, and decision-making tools for businesses in the e-commerce, retail, finance, advertising, cyber security, real estate, pharma, and insurance industries.
DATAFOREST apply business automation, large-scale data analysis, and advanced software engineering to improve performance outcomes for organizations and create added value for clients and shareholders. Good data governance is key to a successful analytics strategy.
The DATAFOREST APA platform offers a modern, tech-enabled solution that makes data accessible and actionable. From surveying to predicting, from understanding to automating, and from price optimization to inventory management, DATAFOREST builds next-generation data-driven applications for analytic process automation.
Streamlining Business Processes with DATAFOREST.ai APA Platforms - BOOK FREE Infrastructure Audit
The DATAFOREST team assess your stack, identify shortfalls and recommend improvements to performance optimization and infrastructure cost reduction.
Try it now!
One of the most striking features of the team is the diversity of our experience. The team includes several black belts in data science and analytics, highly capable experts who can can provide a broad range of services. Common tasks include website visitor profiling, business process redesign, data cleansing and normalization techniques, data mining, predictive analytics, prescriptive recommendations, and the design of customer-driven algorithms using machine learning techniques.
If you'd like to learn more, or request a demo of one of our systems, please just let us know. We'll be happy to help. Contact Us Now!