Advanced Analytics

Self-Service Advanced Analytics

Orbit’s advanced analytics solution has been developed to help business users plan the future with predictive analytics.

The velocity of data creation has crossed human comprehension. To be able to leverage this data meaningfully to forecast operational outcomes, model business scenarios, and improve strategic planning, augmented analytics driven by AI/ML languages is much needed.

Orbit applies sophisticated techniques to help make predictions and spot trends in your data. Built as a self-service analytics tool, it harnesses the power of Python, R, and SQL to help you convert your static data, useful for day-to-day operations, into dynamic insights.

Discover trends, patterns, correlations, and outliers in your data to predict the future of your business and devise strategies for greater success. Orbit also provides an enterprise-wide view, aggregating data from all your data sources into one format, making analysis quicker and easier.

Orbit’s self-service business analytics gives you the flexibility to interpret data without help from IT. In just minutes, you can aggregate data from any source into reports, dashboards, and visualizations. Then, you can extract valuable insights that help you drive innovation, boost operational efficiencies, and increase revenue.

Python is an ideal fit for data analysis as it comes with libraries that have reached maturity, offering flexibility and performance along with functionality. It is easy to learn, is open-source, and can be easily ported to various platforms. It is especially ideal for data analysis as it can handle repetitive tasks and data manipulation.

By tapping into Python, Orbit frees you up to focus on providing value addition from the insights gained to facilitate improvements and efficiency. You can use your data to create better business strategies rather than be bogged down by repetitive tasks. You can also benefit from the wide choice of libraries in Python such as NumPy, Pandas, and Matplotlib, to aid you in data analysis.

Live Access to Your Financial Data

The only complete solution for Oracle Cloud ERP Financials reporting, GLSense provides built-in Microsoft Excel integration with leading ERP software. Directly integrate your ERP financial system with Excel to build financial statements and expedite your reconciliation and close processes.

Orbit Analytics Integration

Real Time Drilldown to Your Subledger Data

Improve your reconciliation process and achieve a faster period close with complete drilldown from balances to subledger with hundreds of pre-built reports.

Data Security and Governance at Orbit Analytics

Simple and Secure Report Distribution

Do everything inside Excel. Fast, easy distribution of financial reports without switching between applications.

For Cloud Financials, EBS, and NetSuite

Build financial statements from live data in Oracle Cloud Financials, Oracle EBS Financial reporting, NetSuite, and more.

Python Scripts

Orbit allows you to leverage the Python libraries embedded within its BI server. This gives you the ability to create predictive analytical models with the metadata layer, as well as build reports with advanced analytical visualizations. Having the ability to access Python within Orbit is important because it is one of the most common programming languages used by data scientists.

Python is an ideal fit for data analysis as it comes with libraries that have reached maturity, offering flexibility and performance along with functionality. It is easy to learn, is open-source, and can be easily ported to various platforms. It is especially ideal for data analysis as it can handle repetitive tasks and data manipulation.

By tapping into Python, Orbit frees you up to focus on providing value addition from the insights gained to facilitate improvements and efficiency. You can use your data to create better business strategies rather than be bogged down by repetitive tasks. You can also benefit from the wide choice of libraries in Python such as NumPy, Pandas, and Matplotlib, to aid you in data analysis.

R Scripts

R is one of the most popular programming languages used by statisticians. Having in-built integrations with R and Python is one of Orbit’s most important capabilities.

With Orbit, you can look at your data and then model different input variables to see outcomes based on various situations. For example, how would your sales be impacted in six months if you added reps in an understaffed region and a new competitor entered the market?

Whatever the size of your dataset and however millions of lines it may have, Orbit’s use of R makes it easy to process them quickly. R’s special data structures can help handle missing data and statistical factors better. Most importantly, it can access spreadsheets, databases and other data formats on the cloud or the local server, aggregate them in one format and provide a unified view.

SQL Scripts

Since Orbit is database agnostic, it integrates with all of your key business systems and allows you to aggregate information from multiple data sources. By maintaining data tables as components, Orbit executes a best-path approach that allows SQL to fetch queries and extract data efficiently.

This empowers you to quickly build interactive reports, dashboards, and visualizations that support multidimensional predictive analysis. For example, you can combine financial and sales data to gain deeper insights into your projected gross revenue. Then, you can layer in data related to your inventory and customer support resources so that you can predict its impact on your profit margin, based on sales volume in multiple scenarios.

The greatest advantage of using SQL is that it allows you to access data wherever it is stored rather than copy it into other applications. This data is also easier to audit and replicate, reducing the chances of errors in cell-based formulae.

Augmented Analytics

Augmented Analytics is a term that was introduced in 2017 in a Gartner Whitepaper. It refers to an approach of data analytics that uses Machine Learning and NLP to automate analysis, a process normally performed by a data scientist.

Orbit’s augmented analytics capabilities enables the business user to automate data preparation, insight discovery, and visualization. Orbit’s pre-built reports help eliminate several steps in the traditional data and BI value chain. Using a combination of statistical and linguistic technologies, Orbit’s advanced analytics solution helps convert big data into actionable insights, in some key areas of decision making.

It helps with the auto-visualization of certain data patterns, predictive and prescriptive analytics, and makes it really easy for the business user to capture real-time insights, without the help of IT.

For Finance

Reconcile and close faster with instantly refreshable drill-down reports inside Excel.

For HR

Access all of your employee data in one place to predict your staffing needs and improve performance.

For Supply Chain

Make real-time forecasts to reduce your costs, meet customer demand, and drive growth.

GET THE WHITEPAPER

Whitepaper

Transforming Your Data for Analytics: Three Options

Webinar On Demand

Python 102 – Data Mashing & Multi Data Source Analysis