Data Analytics Integrity Challenges to Implementation of the Automated Data Collection Processes

March 12, 2020

In recent months, my company (Baron Consulting) has been proactively involved in setting up Data Collection Systems for a range of Private and Public Organisations we are servicing. Some of the data collection challenges have already been discussed in our recent Raw Data Collection 2020: Principles and Challenges White Paper. While the RDC (Raw Data Collection) paper analysed the current state of the everchanging Data Collection requirements, it did not have the scope to address technicalities of the RDC processes along with the specific Data Collection tools and methods. The purpose of this paper is to fill the void by looking into implementation of the automated data collection processes.

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Blue Guava - Predictive Analytics

Blue Guava helps enterprises take advantage of the power of advanced Predictive Analytics through real-time, enterprise-level solutions using best practice business, technology and analytical methodologies. We’re an incredibly results-driven organisation. In fact, our whole business model relies on our clients realising tangible results from our services. The field of advanced analytics has long been restricted to the realm of quantitative analysis and actuarial science in Insurance and Banking & Finance and has been beyond the reach of most organisations. The hype around Big Data is not going away anytime soon. The truth, however, is that there is an enormous amount of hidden value in the data that you already have. If you can’t currently extract this value out of your small data, how will you tackle this brave new world of exponential growth in data? Our mission is to “make advanced analytics more accessible” and to use your data to skyrocket your sales and growth. Every business ca

OTHER WHITEPAPERS
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Introducing Apache Druid

whitePaper | January 31, 2020

Many companies have invested heavily in specialized enterprise data warehouses (EDW) and Extract, Transform and Load (ETL) technologies to analyze their operational data. But these technologies were never designed to be truly real-time.They were originally built for batch, and that original design limits how real-timeEDWs and ETL can become. They were also designed to support a focused group ofanalysts, not a larger group of employees spanning operational functions, or even partner and end customers.

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Prescriptive Security for Financial Services

whitePaper | November 15, 2019

The potential of artificial intelligence to transform business performance is only now starting to be more widely understood in Financial Services. This is nowhere clearer than in the security domain, where the fusion of big data, advanced analytics and machine learning holds out the promise of startling improvements in cyber defenses through the introduction of Prescriptive Security.

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GBM-Security

whitePaper | November 15, 2019

We are living in an era of digital disruption. Multiple industries are being disrupted, or fear being disrupted in the near future. Business models are evolving to cater to the dynamic markets and digital transformation that seems to be the answer to changing business models. Digital transformation is rapidly becoming a key priority in most industries, as organizations adapt to changing markets by leveraging technologies to build IT-centric business models. In general, organizations are using digital transformation to reach their goals of achieving greater agility, improving operational efficiency, improving customer experiences, and developing new revenue streams.

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Evolving Role of Data Scientist in the Age of Personalization

whitePaper | March 12, 2020

This point of view is an exploration of the possibilities engendered by rethinking the role of data scientists in the wake of industrial revolution. It might be claimed that current trends in industrial revolution reflect a paradigm shift towards data centric processing with data science playing an increasingly critical role. This point of view also explicitly highlights the potential role of Data scientists as an emerging phenomenon, and then to show some of the benefits that this role can bring as we move towards industrial disruption

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BARC Score Enterprise BI & Analytics Platforms

whitePaper | August 12, 2021

This BARC Score report will evaluate BI & analytics platforms on a range of features, from data visualization capabilities to semantic modeling abilities, performance and speed to automation capabilities.

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Enterprise analytics: Ideal vs. Reality

whitePaper | September 28, 2021

Read on to learn how the Cloudera Data Platform accelerates your on-premises data analytics operations in a manner reminiscent of the cloud, unlocking flexibility, scale, and power from your traditional, on-premises data center.

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Spotlight

Blue Guava - Predictive Analytics

Blue Guava helps enterprises take advantage of the power of advanced Predictive Analytics through real-time, enterprise-level solutions using best practice business, technology and analytical methodologies. We’re an incredibly results-driven organisation. In fact, our whole business model relies on our clients realising tangible results from our services. The field of advanced analytics has long been restricted to the realm of quantitative analysis and actuarial science in Insurance and Banking & Finance and has been beyond the reach of most organisations. The hype around Big Data is not going away anytime soon. The truth, however, is that there is an enormous amount of hidden value in the data that you already have. If you can’t currently extract this value out of your small data, how will you tackle this brave new world of exponential growth in data? Our mission is to “make advanced analytics more accessible” and to use your data to skyrocket your sales and growth. Every business ca

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