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Everyone’s been talking about Big Data for decade now and how this data can be used for better strategic decision and more advanced analytics, but only few companies have in reality mastered their data in a way that

1) Makes all data easily accessible and

2) Improves forecasting in making decisions with data.

The concept of a data lake is becoming basis for many organizations as they try to create more and more value out of their data sources. This changing trend toward a data-driven business approach targets a growing variety of data, and it’s more crucial than ever to include all data assets as part of the next-generation data architectures and BI reporting dashboards. To truly “master” all of a company’s data in an environment where they react quickly to business needs, companies must first liberate all enterprise data, specially hard-to-access data from old platforms like the mainframe which houses the most critical data assets such as clients data. Organizations must then integrate these core data assets with the emerging new data sets from cloud platforms.

Bilytica’s Business Intelligence Services in Namibia provides state of the art services for your organization irrespective of the size of your workforce. You can manage your clients, services, market capital and opportunities with wide range of reporting tools. Below are a number of features companies can benefit from when embarking on a project to master their data by using Bilytica’s Big Data Analytics Solutions in Namibia :

– Ensure easy and more secure access to all data assets and visibility to data lineage as the data is populated in the data lake.

– Choose a product-based approach to custom coding for repeatability, simplicity, and output.

–Assurance that the selected tools and products can adapt to a rapidly changing technology stack, and can integrate and keep up with the pace of the Big Data stack

– Assurance that the tools and products can interoperate and leverage open source frameworks for advanced analytics.

– A streamlined, standardized, and more secure process to collect, transform, and distribute data.

– Compliance and security requirements from the very first day and not after the fact, especially those in highly regulated corporations and those that house sensitive customer information on the mainframe.

– Make data quality main priority. Mastering your data needs capability to discover data reports, create business rules and use these rules to validate, match, and cleanse the data. Automation of all initial steps and the ability to authenticate and cleanse as you inhabit the data lake becomes critical as organizations become more data centric.