Data Warehousing & Data Visualization

Data Warehousing & Data Visualization

Data Warehousing & Data Visualization

Having a clear data strategy is absolutely vital when you consider the sheer  volume of data that is available these days. Collecting data without considering what you want to do with it is useless. A good data strategy is not about what data is readily or potentially available – it is about your business objectives, and how and what data can help achieve your targets. It is also important to remember that no one type of data is inherently better than any other type. Using data strategically is about finding the best data for your company, and that may vary from business to business. With so much data available these days, the trick is to focus on finding the exact, specific pieces of data that will help you make the most optimum decisions. Data Pilot will help you in understanding your business problems and devising a long term data strategy accordingly. By doing so, we will not collect just any data, but we will collect the RIGHT data, resulting in improved and speedy decision making for your business.

Data Visualization

Data Visualization is the art of making sense of data using visual elements like charts, graphs, and maps. We have data visualization experts who build meaningful insights from your data to help you make better decisions through data. Our data storytelling skills aid in building effective dashboards for businesses. When building dashboards, we build visuals to reduce cognitive load, cognitive friction and increase data-pixel ratio. Moreover, it is VERY important to pick the right chart for each KPI to communicate insights effectively. We have expertise in Tableau, Power BI, Google Data Studio, Metabase, Apache Superset, Holistics etc.

Business Intelligence

It is important to understand that reporting should not be done on top of your transactional database. In the start, basic reports can be built on your main database but to enable analytics across the organization, it’s important to have a Data Warehouse. We have expertise in converting your transactional and operational data stores (OLTP) to a Data Warehouse (OLAP) in order to build dashboards for data driven decision making across your organization. Based on your reporting requirements, we design an optimized data warehouse model using star or snowflake schema to fulfill your reporting needs which serve all departments across the organization. On top of the data warehouse, we build a presentation layer for business intelligence which entails building dashboards to aid decision making for business users. For data warehousing, we have expertise in HP Vertica, Microsoft SQL Server, Oracle, Snowflake, MySQL, PostgreSQL, Google BigQuery, AWS Redshift. For enterprise BI, we have expertise in OBIEE, IBM Cognos and Pentaho.

What is data warehousing architecture?

A data warehousing architecture is a centralized repository that defines the data communication presentation and processing. Although every data warehouse is different, they are distinguished by standardized components.

Data Warehouse is essential to provide data to Business Intelligence (BI) tools and generate reports. It stores data using ETL (Extract Load Transform) from various sources like databases, cloud storage, and APIs among others.

AI technologies have resulted in process automation and process discovery. In this digital age, making data-driven decision-making is essential for every enterprise for digital transformation. AI and machine learning can extract meaning from data when the answers are clearly defined. Moreover, they can also transform exponentially dynamic unregulated and regulated data into insights, behaviors, values, and profitability improvements. Similarly, advanced machine learning and big data can assist AI to take a focal point.  

How Does ML & AI Help Your Business?

Machine learning and AI can help your business decrease equipment breakdown through preventative maintenance. Furthermore, it can help you increase profits by analyzing business performance in detail. The predictive model can predict purchases, revenue and probability, and several variables for better decision-making. With our machine learning consulting services, you as an enterprise can leverage customer data to create valuable customer profiles and thus enhance brand loyalty.

Machine Learning Solution:

We have strong expertise in building machine learning models which demonstrate business value. We start with an exploratory analysis to make sense of the data and pick important features to predict a specific outcome (target outcome within the dataset. For model evaluation, we choose the right metric based on the dataset and business outcome. Due to the bias-variance trade-off, it is very important to ensure that the machine learning model is balanced in terms of the trade-off to avoid over or undercutting and help the business in predicting the right outcome to demonstrate maximum business value.   Through Deep Learning, we have demonstrated the ability to build deep learning models (using PyTorch, TensorFlow, and OpenCV) using tabular data and images. Moreover, we have strong expertise in building computer vision models using deep learning and transfer learning for problems like object detection, facial recognition, image classification, and so on.    Our Machine Learning Roadmap:

You can gain a competitive edge over your rivals by adopting state-of-the-art data practices. Moreover, we can create end-to-end machine learning solutions for your specific business needs by using intricate statical methods and various ML models and algorithms such as Deep Learning.

We have expertise in Machine Learning, Computer Vision, Natural Language Processing (NLP), Deep Learning, and Chatbots. We adopt a holistic approach to developing robust AI & ML solutions that entail the following phases: 1. Learn: Develop an understanding of the business model and problems faced. 2. Educate: Explain AI technology and develop a common ground of possibilities for the business. 3. Ideate: Find solutions and prioritize them for the short-term and long-term. 4. Develop: Formulate an action plan to transform the business with AI. 5. Implement: Ensure the organization embraces the technology by providing a thorough change management plan.