Artificial Intelligence and Machine Learning Analytics Consulting Services
Analyzing Large Volumes of Data
Organizations are faced with tremendous pressures in the marketplace – to be more innovative, increase their speed-to-market, save time and money, be more productive, delight their customers, and more.
Business leaders are looking at ways to meet all these challenges and increase their overall competitiveness. One significant approach they are looking at to accomplish these goals is through advanced data analytics, and utilizing “artificial intelligence,” or “AI,” and “machine learning” or “ML,” a subset of AI.
With the exponential growth of data continuing as each day goes by, there is no shortage of raw material that can feed their analytics platforms. However, they need a viable method to be able to quickly and accurately analyze large volumes of data to garner insights and allow them to make timely decisions regarding almost every facet of their business.
What is AI and ML in Data Analytics?
AI in data analytics allows large amounts of data, coming from a myriad of different sources, to be very quickly processed and analyzed faster and more accurately than a human brain would be able to, to detect trends more easily, patterns, etc. Platforms and tools that use AI technology also have the potential to make adjustments.
ML, a subset of AI, employs computer systems that can learn, change and improve over time without being programmed to do so. It does this through the use of statistical models and algorithms to analyze and draw inferences from the data.
Today’s ML systems perform fundamental functions:
- Evaluate data to describe what happened – this function is ‘descriptive;’
- Evaluate data to predict what will happen – this function is ‘predictive,’
- Evaluate data to make suggestions about what can or should happen – this function is ‘prescriptive.’
Datavail AI and ML Data Analytics Consulting Services deliver the expertise to make assessments, road maps, implement and integrate systems and provide managed services to support organizations in their AI and ML data analytics initiatives.
AI and ML Analytics Consulting Services from Datavail
Datavail can apply our extensive experience and knowledge to helping with a wide variety of services including:
Assessments
Performing an assessment of your data management and analytics environment and providing you with a total cost of ownership (TCO) evaluation. This includes evaluating your entire current platform to determine if your system – from data ingestion, data storage through visualization processes – can support AI and ML capabilities.
Strategic Consulting and Roadmaps
Creating a complete data management and analytics strategic roadmap, to provide a strategy for an advanced analytics platform and capabilities, including AI and ML.
Application Implementation and Integration
Includes architecture, design and deployment of an advanced data analytics system to implement and integrate AI and ML processes and technologies.
AI and ML System Development
- Conduct business analysis.
- Gather data and determine the viability of the potential predictive model.
- Prepare the data for the appropriate machine learning algorithm.
- Evaluate the data.
- Use the model to see how well it predicts information.
- Manage and maintain the machine learning models through the entire data science life cycle going forward.
Managed Services
Providing post-implementation continuous support 24/7/365 for your AI/ML environment.
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What are the Benefits of AI and ML in Analytics?
The ability of AI systems to analyze data autonomously has multiple business benefits. This includes reducing the labor cost of data scientists and other highly paid and limited-availability analytics professionals. Additional benefits of AI and ML in data analytics, just to name a few, include:
Increased innovation and speed-to-market
AI and ML analytics tools perform analysis to identify opportunities to make updates to existing product features as well as creating new products.
Better customer experience
Use AI analytics tools to determine what customers are looking for—acquire them, retain them and cultivate their loyalty.
Successful marketing campaigns and sales
Create targeted campaigns with AI/ML data analytics to focus on the “right” prospects and leads, as well as current clients to cross-sell/up-sell.
Improving revenue and growth
Predict business outcomes, discover opportunities to personalize customer services and determine corporate strategies that have the potential for the best success.
Improving efficiencies
Save time and money by making changes and enhancements to businesses processes and workflows.
Lowering overall business costs
Find opportunities to optimize production investments, reduce waste of capital assets, and ensure higher, more reliable levels of quality control across the enterprise.
Managed Services
Providing post-implementation continuous support 24/7/365 for your AI/ML environment.
Why Datavail for Your AI and ML Data Analytics Initiatives
Datavail’s Data Management and Analytics practice is made up of hundreds of experts who provide a variety of data services including initial consulting and development, designing and building complete data systems, as well as ongoing support and management of database, data warehouse, data lake, data integration, and virtualization and reporting environments.
We can also implement AI/ML technologies and tools to fit your unique business needs including development, customization and integration as well as post-deployment management and support 24/7/365 of your advanced analytics platform.
Our Data Analytics consulting services allow companies to integrate their data from disparate internal and external sources and allow it to be transformed so that it is accessible, reliable, insightful, actionable, and used to make better decisions.
The data analytics AI/ML services Datavail provides can allow companies to use their data to improve operational efficiency, find competitive advantages, enhance financial effectiveness to increase revenues, decrease costs, and more.
Partnership
Working as an ongoing partner with your team to ensure success of the overall program – this is not a transaction but a journey.
Consultative
We bring expertise in various focus areas and technologies relevant to your solution to lead and own the solution.
Intellectual Property Based
We do not reinvent the wheel with each engagement, we bring proven methodologies, templates, and architectures to jump-start your initiative.
Forward Thinking
We invest in IP, labs, technologies and emerging platforms.
Build → Run
Our approach is to not only build the solution but to build a solution that we can support and leverages our existing support model.
Tips for Machine Learning Model Selection
The best ML model can be viewed from different angles: performance, speed to deployment, easier training, etc. Learn how to choose the best model for your buisness in our white paper.
Use Cases for AI and ML in Analytics
Today’s businesses deploy AI and ML in their data analytics systems to address several common concerns that affect most companies:
Provides real-time data to drive real-time decision-making.
Before the advent of AI/ML, companies made decisions based on data that was sometimes collected months earlier. The ML system can pull information from streaming data sources, so its analysis is based on factors and events that are happening in real-time.
Predicts customer behavior.
AI/ML systems can analyze consumer behaviors and provide relevant and critical insights to justify corporate investments. A well-designed and deployed ML model can inform leadership about product popularity, pricing opportunities, and production improvements, among many other options, simply based on how customers interact with the enterprise.
Directs product development decisions.
An unsupervised AI/ML system will analyze data sources to identify patterns in production systems that might indicate product popularity, production problems, or other relevant aspects of production resources. Leaders use ML results to increase or decrease production lines, modify existing products in response to consumer demand, and even eliminate product lines altogether.
Can also be trained to enhance production values.
AI/ML systems can be of high value, especially in the manufacturing arena. Companies use ML systems to analyze the data regarding the purchase and use of production equipment to schedule appropriate maintenance dates and avoid costly shutdowns due to failed machinery. The practice also reduces the cost of maintenance by reducing the need for urgent or emergency repairs.
AI/ML systems are also commonly used to enhance corporate security.
Just as it can analyze consumer behavior, the ML system can also analyze internal networking behaviors to find anomalies that might indicate a breach or fraud instance.
For skilled consulting, implementation and managed services for your advanced analytics artificial intelligence and machine learning initiatives, complete and submit the form on the page, and one of our data experts will reach out to see how we can help you reach your business goals.
Further Reading
How Do I Know My Machine Learning Data Model is Good
This presentation will demonstrate the most commonly used ML techniques and algorithms, and their corresponding Data Model evaluation metric. Then, we will use Oracle Analytics Cloud (OAC) to provide a comparison by using a sample data set.
Why You Should Embrace Machine Learning – You Can’t Afford Not to
Recent research indicates that most companies (80%!) were unsuccessful in fulfilling their aspirations of implementing Machine Learning (ML) systems in 2021.
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