A New World of Flexibility and Functionality with Cloud Pak for Data
Data silos, business fragmentation, redundant operations, uncertainty, interoperability challenges, costly bespoke integrations, etc., are plaguing modern-day organizations. Even with powerful solutions like IBM planning analytics, and IBM Watson at their disposal, businesses find it challenging to cope up with the fragmented nature of the workflow, and understandably so.
While such solutions are world-class, they work individually and cater to the requirements of departments rather than the whole organization. This is where IBM’s Cloud Pak for Data becomes potent. Cloud Pak for Data, or as IBM puts it, “One platform,” promises to liberate an organization from data silos and provide access to new opportunities. The platform makes that possible with gleaned insights from holistic data analytics.
With the ability to facilitate 8x faster data access, 65% reduction in ETL requests, 65-85% reduction in costs and risks, Cloud Pak for Data is an ideal solution for businesses looking to implement an end-to-end data-driven ecosystem. To that end, let’s dive deeper into Cloud Pak’s ability to expedite a flexible, streamlined, and integrated data-driven enterprise strategy.
Platform Integration — Data Unification
Forrester reveals that more than 50% of organizations suffer from poor integration of the tools at their disposal and 60% struggle to unify data analytics at a more granular level. IBM Cloud Pak for Data treats such ailments by significantly slashing data silos. At the crux of IBM’s solution lies data virtualization that works to unify data, centralize the data access control, and scale data analytics as per requirements.
Technically, data virtualization entails the development of a constellation (self-balancing database repository) that accommodates the connection of disparate data sources. The word “disparate” covers literally any of the popular data sources: Apache Hive, IBM Db2 Big SQL, Netezza, MariaDB, SQL Server, MySQL, Oracle, IBM Informix®, etc.
Here’s how the data virtualization process helps:
- Each data source’s power can be leveraged in real-time, which tremendously reduces latency in accessing data.
- Similar schema can be identified and visualized in the form of a unified schema. Suppose the marketing data is stored in ten different databases. Data virtualization will combine these ten different schemes into a unified schema for querying.
- Systems like Tableau and IBM Cognos® can be connected regardless of the querying language as data virtualization supports conversion of the SQL dialects.
IBM Cloud Pak for Data thus allows for seamless access to unified data. The application of data virtualization best suits time-sensitive scenarios where a business has to deal with massively distributed datasets from several data sources. Considering that these data sources exponentially grow, conforming to Cloud Pak is a viable option even if the current scenario doesn’t involve accessing distributed data.
Independent Scaling -— Unmatched Analytics
Business complexity is linked to the 4Vs of big data. This complexity is characterized by data duplication, fragmented management, high costs, and security leaks. Cloud Pak for Data tackles each of these issues through Netezza® Performance Server.
Netezza® Performance Server, which is a cloud-native AI system, enables unprecedented levels of deep analysis. IBM has powered Netezza® with a multi-petabyte scaling system that allows it to identify patterns and extract insights from otherwise massive volumes of erroneous data.
Besides, Netezza® Performance Server follows the Cloud Pak services ecosystem, where it leverages analytics capabilities of 45+ tools and templates (both from IBM and third-party developers). The aforementioned data virtualization capabilities allow it to query data across disparate sources.
Besides, Netezza® Performance Server follows the Cloud Pak services ecosystem, where it leverages analytics capabilities of 45+ tools and templates (both from IBM and third-party developers). The aforementioned data virtualization capabilities allow it to query data across disparate sources.
- As the data volume grows, the on-premise, public cloud, or private cloud environments can be scaled to accommodate the same.
- Cloud data warehouse runs 24*7 with no downtime whatsoever thanks to infinite capacity scaling and fault tolerance capabilities.
- Netezza’s deployment can be hybrid, meaning businesses can switch between on-premise and cloud-based on their preferences.
DataOps as-a-service — Journey to AI
Market dynamism demands a solution that follows the pay-as-you-go approach, something that IBM Cloud Pak for Data complies with. The previously mentioned scaling capabilities are also a testament to the same, with the ability to scale the environment based on requirements being central to the discussion. But there’s much more when it comes to realizing Cloud Pak’s as-a-service capabilities. Most of these relate to supporting DataOps and helping a business transform using AI to the best effect.
Here’s how Cloud Pak optimizes DataOps:
- The legacy digital architecture can be transformed into a cloud-native system that solves the problem of storing, managing, and querying big data.
- Data cataloguing can enable one view for the entire operating system so that each organizational entity can access data and share useful insights within or across departments.
- IBM Watson Knowledge Catalog can scan and profile data to prevent security leaks and ensure effective governance.
Here’s how Cloud Pak manages the inclusion of AI:
- It makes Watson Studio accessible for data analysis and visualization.
- It allows for the development of prediction-making custom models on the back of Watson ML.
- It equips a business with Explainable AI for automating model functioning. The case for the previously defined Watson Knowledge Catalog also contributes immensely to IBM’s endeavors of helping organizations incorporate AI.
Conclusion-
From integrating tools/platforms to providing a unified data analysis experience, Cloud Pak for Data manages to stand out as a go-to solution for a flexible, scalable, and intelligent enterprise growth strategy.
Apart from these, Cloud Pak addresses the simplicity of usage and cost-effectiveness alongside ensuring unmatched system security, data governance, and data management capabilities.
Learn more about Cloud Pak for Data to discover how it can help your business better leverage data and accelerate the journey to AI.
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