Teradata recently announced ClearScape Analytics as part of the Teradata VantageCloud offering. Let me share with you first what ClearScape is and second, how you can benefit from it.
ClearScape Analytics refers to the analytical capabilities built into Vantage. It provides end-to-end analytic capabilities that unveil the full view of your data and deliver the sharpest, most precise picture of where to go next.
To do this ClearScape Analytics delivers a solution that can best be understood by looking at three areas of value.
ClearScape Analytics offers following capabilities.
- Highly Optimized In-Database Analytic Functions: ClearScape Analytics has comprehensive in-database analytic functions for advanced analytics and machine learning. These analytic functions are highly optimized to work on large-scale data. These functions can help solve complex AI/ML use-cases such as dynamic pricing, demand forecasting, fraud detection, dynamic supply chain and many more.
- Leveraged from Languages & Tools of Choice: All ClearScape Analytics can be leveraged with enterprise tools of choice as well as a wide range of partner integrations. This means that data scientists can leverage the power and scalability of Teradata Vantage directly through their preferred tools.
- Operationalized at Scale to Drive Transformative Results: All analytics can be operationalized at scale. Analytics can be developed natively using in-database functions as well as externally developed analytics, which can be imported inside VantageCloud for operationalization purposes. This ensures that AI/ML initiatives lead to business outcomes and successful digital transformation initiatives.
With the understanding of ClearScape Analytics’ end-to-end functionality, we can now turn to how you and your organization can benefit from it. The non-exhaustive list of people getting value from ClearScape Analytics includes:
- Chief Analytic Officer (CAO)
- Line of Business Leader
- Analytic Platform Owner
- Head of Data Science, Data Scientist/ML Engineer
- Business Analyst
- Data Engineer
Now let’s see how Teradata ClearScape Analytics can be beneficial to these people.
The CAO can use ClearScape Analytics to accelerate analytic-led digital transformations
The CAO’s main objective is to ensure that digital transformations are analytic led. In the current digital age, AI is becoming ubiquitous and central to digital transformation. Enterprises that can pick up the pace and accelerate AI initiatives will be the ones that outshine and outperform the competition.
The way to tangibly accelerate AI is when it becomes part of day-to-day, data-driven decision-making. With ClearScape Analytics, businesses can have Descriptive, Predictive, and Prescriptive analytics all on the same platform. For example, retail business users can have past sales reports as well as forecasted sales with a single query. Or a financial business user can have a 360° view of their customer as well as customer churn probability within the same information context. Such capabilities ensure that AI, as well as BI capabilities, are used on a day-to-day basis, which leads to analytic-led business transformations
The Line of Business Leader can use ClearScape Analytics to surpass their financial and non-financial KPIs
The current business environment faces multiple disruptive factors such as supply chain disruptions, financial market instability, and technological disruption, to name a few. Disruptions have become more frequent over the last 10 years, and it is expected that they will persist.
Data is the core of improving business resilience to the macro environment. Proper user of AI/ML leads to 2x revenue and profit impact. For example, scenario planning, forecasting, dynamic pricing, and advanced customer interaction can help create a dominant business strategy to succeed in turbulent times.
Business heads are constantly looking for ways to improve their business using data and AI/ML. ClearScape Analytic can help build business solutions that can directly contribute to financial and non-financial improvements through data and analytics. Some examples of such business outcomes are fraud prevention, dynamic supply chain, digital identity management, predictive maintenance, and many more
Analytic platform/product owners can build robust, scalable, low TCO analytic platforms with ClearScape Analytics
In recent years, we have seen the Analytic Platform/Product Owners role becoming important for many industries and not only for the software industry. Telco, Retail, Banking, Automotive, Entertainment, Logistics, Transportation, and Hospitality enterprises are creating analytic platforms which can help elevate the customer experience through the use of AI/ML. Analytic platforms are also enabling traditional businesses to become a digital business.
Analytic Platform/Product Owners can rely on ClearScape Analytics to build a robust, scalable platform with a low TCO. As ClearScape analytics is built upon Teradata core technologies such as smart scaling, workload management, and adaptive cost optimizer, the Analytic Platform/Product Owners can use ClearScape Analytics to build analytic platforms and products to achieve their SLA and TCO targets.
Data scientists and ML engineers can solve large-scale analytic challenges with ClearScape Analytics
Breakthrough digital transformation requires solving large-scale analytic challenges. Data scientists and ML engineers are key to solving large-scale analytical challenges with various AI/ML algorithms.
Large-scale analytic challenges are not difficult to find in large enterprises. Forecasting millions of product sales, real-time fraud detection on millions of simultaneous web sessions, or IoT robot anomaly detection on billions of sensor readings are just a few.
With ClearScape Analytics’ comprehensive in-database functions and an in-database machine learning pipeline, data scientists can help apply various algorithms to large-scale data. ClearScape Analytics will ensure algorithms are executed in an optimal way, with minimum data movement.
The data scientist will also like the fact that they can use their tool of choice such as Dataiku, AzureML, and Amazon Sagemaker as well as leverage the power and scalability of ClearScape’s in-database analytics. They can also use the Bring-Your-Own-Model (BYOM) approach to import external AI/ML models for operationalization purposes as well as ModelOps to monitor the models.
Business analysts can use ClearScape Analytics to convert data into powerful insights
The key to digital transformation is to understand how data will be able to deliver the breakthrough transformation. This is done by people such as business analysts, who have competence in both data as well as business. The data needs to be explored at scale to see how it can be useful in solving complex business problems which can lead to digital transformation. With an ever-growing amount of data, the data exploration must be done at scale as well as across various data formats.
Business analysts are one of the key personas who help convert data into powerful business insights. They can use ClearScape Analytics for various in-database functions such as path analysis, time-series, geospatial, text analytics, and 4D analytics on a massive amount of data and convert it into powerful insights.
Here are a few examples of how business users can use ClearScape Analytics to get powerful insights:
- Path analysis can help understand patterns in customer behavior.
- Time-series analyses are useful to analyze trends in sales such as seasonal trends. Geospatial analytics is very useful for location analysis, route analysis, and geographic density analysis.
- Text analytics can be used by business analysts to understand the sentiment in customer comments.
A business analyst can use ClearScape analytics functions in practically infinite ways to get powerful business insights and contribute to making the enterprise data driven.
A data engineer can do efficient data provisioning with ClearScape Analytics
The data engineer profession is on the rise. As they provide the data from various sources, they are the critical link in the entire analytic chain. If data is not provisioned and not prepared, none of the analytics and digital transformation can happen.
Data engineers can rely on ClearScape Analytics' powerful data integration and data preparation functionalities to help them in their roles. As ClearScape Analytics is tightly integrated with Teradata data fabric, it is going to facilitate the data engineer’s job.
Bottom line: ClearScape Analytics provides robust functionality giving people across the organization the ability to efficiently execute their roles in the analytics process on a common platform. This gives the larger organization not only a repeatable and efficient process but a clear view of where to go next.