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SAGE Technologies: Un-freezing Data Lake Conundrum


Data lake implementations can turn problematic and do not often deliver the promised return on expensive investments. It is common for big data implementations to result in a ‘frozen data lake’. It is a state where business users are unable to access the Hadoop-stored data. They cannot make accurate requests for useful information, without encountering raw content. An ineffective data lake shuts off access to valuable data insights behind highly-technical IT users.
“With data lake, most customers have big expectations. This was an obvious solution to storing its variety of data sources—semi-structured reports, unstructured banker’s notes, plus volumes of spreadsheet data— in their native formats, which they could not do in a traditional data warehousing scenario.The challenge is how to make best use of the disruptive technology to drive value from big data,” says Charles Kwan, Sales Director, SAGE Technologies.
SAGE Technologies promises to ease the roadblocks that come with data lake implementations, helping it deliver its true potential. Their suite of solutions includes managed data lake ingestion, data lake inventory, catalog and governance and end user data preparation and extraction.
SAGE Technologies, with its vast consulting knowledge in data warehousing, provides data analytics solutions, transitioning raw data source inputs into outputs for analysis. It enhances solutions with new Hadoop ecosystem tools and self-maintained data lake practices, machine learning, and adaptive intelligence.
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SAGE Technologies’s proven practice and framework on big data management, data governance, and data wrangling helped it carve a niche in the market
SAGE Technologies’s proven practice and framework on big data management, data governance, and data wrangling helped it carve a niche in the market, with deep understanding of client needs. With 18 years of experience in providing BI solutions and specialization in financial services, SAGE Technologies revolutionized the industry with its cutting-edge approach to data lake.
One of the first sectors to adopt data lake are large banks and financial services companies which are constantly burdened with enormous data that hits them from the strange sources. A successful data lake implementation can ease the complexities of their data management. “Successful data analysis relies on accurate, well-structured data that has been formatted for the specific needs of the task at hand. We have multiple new sources of data with different kinds of variety and velocity, which is crucial for financial services companies, to operate and innovate in the ever-changing market with stringent compliances,” explains Dustin Lee, Head of Business Analytics Solution, SAGE Technologies.
One of SAGE Technologies’s clients is a major global bank which wanted to incorporate self-servicing within its business units for better decision making on risks and investments. They built a data lake framework where the challenge was not restricted to merely managing ingestion of data from various sources. The framework had to smoothly allow the user to locate and govern the data pieces distributed in different locations of the data lake. SAGE Technologies used intelligent data wrangling to aid the use of data for analysis and other business purposes. SAGE Technologies also successfully established a data lake and innovation lab for yet another global banking major which operates across a variety of banking areas. The bank now uses the framework across its retail banking, corporate banking, private banking, credit cards and securities brokerage portfolios.
Despite many challenges it brings along with costs, data lake is essential to derive the best of big data solutions in the most effective manner. Successful data lake implementations can be rewarding and bring to light many hidden factors and associations from dark data.
SAGE Technologies is continuously honing its capabilities to enhance its effects in bringing out the best of data lake. With the foundation in place, SAGE Technologies also helps its customers with their business, in the use of big data use machine learning and deep learning, artificial intelligence applications, operational automation and real-time processing and analytics. It is also looking to provide consultancy services for data lake implementations, to ensure that this technology can truly live up to its promise.

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