Transform your organization using the power of insights based on data analytics, to stay ahead of the competition.
Data Warehousing & Data Lakes
Data Warehouse vs Data Lake
A data warehouse is a database optimized to analyze structured data coming from transactional systems and line of business applications. This data is cleaned, enriched, and transformed so it can act as the “single source of truth” that users can trust. A data lake is different because it stores structured from line of business applications and unstructured data from mobile apps, IoT devices, and social media. With a data lake you can store all of your data from many sources without careful designing or cleansing. As organizations mature with their data warehouses, they see the benefits of including a data lake to enable diverse query capabilities, data science use cases, and advanced capabilities for uncovering insights.
Your data is your biggest asset. Having a modern data warehouse at the core of your organization is critical to provide insights to your leadership and your users quickly and securely. Nihilent can help you figure out the best solution for your business. Whether it is in the cloud, on premise, or a hybrid, we can leverage our team’s experience to help you build and deploy your modern data warehouse.
Having a data lake provides a centralized repository to store all of your structured, unstructured, and streaming data, at any scale. This allows the business to consolidate and manipulate data from different sources at a scale far beyond what is traditionally available. An organization can also build applications to harness the power of distributed and scalable compute while providing cutting edge data manipulation, data flow management and data visualization tools to business and IT.
Using historical and current data, and techniques from statistics, data mining, machine learning, and artificial intelligence, we make predictions for the future leading to actionable business decisions and improvement in performance. Organizations have a lot of data which can be used in conjunction with analytics solutions to provide assistance in decision making. Analytics solutions can be categorized into the following types:
- Descriptive Analytics: Using Data Mining techniques to analyze historical data in order to understand trends over time and provide insights on how the future can be approached. Some examples include dashboards for organization’s sales, finance, or operations data etc. Given your data, our Business Intelligence experts can condense it in a way that would help you take critical decisions.
- Diagnostic Analytics: Examines data or content to answer the question “Why did it happen?” and is characterized by techniques such as drill-down, data discovery, data mining and correlations.
- Predictive Analytics: This goes one step ahead of descriptive analytics and pertains to using Statistical, Machine Learning and in some cases AI methods to ‘predict’ or ‘forecast’ future outcomes using all kinds of data, including texts and images. Examples are forecasting future sales, predicting customer behavior based on his characteristics etc. Our team of Data Scientists can help you be future ready by assisting you with the three pillars of predictive analytics: > Optimization > Pattern Identification > Forecasting & Predictive Modelling
- Prescriptive Analytics: Using simulation, optimization as well as advanced analytical techniques to answer the question ‘What should be done?’ Given a situation in the future, what would be the best course of action, taking into consideration the likely outcomes of each decision? Examples include equipment maintenance, pricing of commodities like oil and natural gas whose price fluctuates with time.
Contact Nihilent today to learn about our Data Platform Modernization Assessment and Proof of Concept to help transform your organization using the power of insights based on data analytics to stay ahead of the competition.
Bring together all of the data you need to gain insights and deliver intelligent actions that improve customer engagement, increase revenue, and lower costs by analyzing massive amounts of data in real time.
Data volumes are exploding. By analyzing a diverse data set from the start, you’ll make more informed decisions that are predictive and holistic rather than reactive and disconnected.
Nihilent can help you organize and make your big data accessible for many types of solutions including:
- Marketing – Gain a competitive advantage by using big data technology to analyze log files, transaction details, and more for an unparalleled understanding of your customers and their needs.
- Manufacturing – Monitor and optimize manufacturing processes by gaining insights into sensor and component data, and integrate with quality and warranty claims data.
- Healthcare – Organize and harness medical device data, intranet and mobile device log files, and operational transaction data.
- Fraud Detection – Gain access to large unstructured log files, operational activity data, and then flag potential fraudulent activities using Machine Learning and Business Intelligence tools.
Drive better insights from your data!
Available on premise or in the cloud, business intelligence analyzes data sets and presents analytical findings in reports, summaries, dashboards, graphs, charts and maps to provide users with detailed intelligence to drive strategic and tactical business decisions:
- Transform your data: Create powerful and scalable data models that turn complex data into actionable insights that can be easily understood
- Access any data: Connect to virtually any data of any size, anywhere in the cloud or on-premise
- Deliver insights anywhere: Let business users connect to and analyze data and share insights
- Modernize enterprise reporting: Scale your reporting solution to deliver insights to thousands of users with an enterprise reporting platform
- Create interactive reports: Quickly generate and share rich, interactive reports that help you visualize and analyze your data
BI Maturity Model
In every organization, there are different levels of BI maturity that come with their own requirements and needs.
To deliver on the promise of fast, flexible and cost effective BI and data warehousing, our experts apply a new approach. We call it ‘Nihilent’s Agile BI Approach’. Unique in the marketplace, this approach aligns the business with IT and combines both the classic and Agile methodologies enabling us to deliver important short and long-term benefits to our customers. Some of the benefits are:
- Decreased time to market for delivery of BI solutions
- Optimized and reduced costs of BI solutions
- Reduced risks and failure of BI projects
- Quickly adapted BI solutions to evolving business needs
- Immediate value of BI seen by leadership
Contact Nihilent to discuss where your organization is on the BI Maturity curve and we will help you lay out a clear roadmap to get you to where you want to be. You can also ask about our Power BI Quick Start if you are ready to implement your BI solution now.
Master Data Management
Data volumes are exploding and one of the greatest challenges all business face is how to organize that data so that it is understandable and usable. Master Data Management (MDM) is a technology-enabled methodology to ensure data assets are uniform, accurate, and unique through consistent identifiers and extended attributes that describe the core entities of the enterprise including customer data, supplier data or product data to name a few. If your data is inconsistent, your results come out incorrect.
Nihilent has deep experience in Master Data Management and can help you create a single source of truth for your master data. For a successful engagement, we typically start with a proof of concept to identify the business drivers and important strategic areas. Next, we identify unique attributes and reduce chances of matching errors. Once this POC is proven out successfully, we move into a more aggressive approach covering the entire data set(s).
Contact Nihilent today to get started on your way to uniform, accurate and unique master data.