Orion Governance, a leader in Metadata Management solutions and the provider of the Enterprise Information Intelligence Graph (EIIG), the foundation for a self-defined data fabric, announced it has entered into a technology partnership with Qlik. This partnership will integrate Orion's EIIG solution with Qlik Cloud to help enterprises tackle their most challenging data problems. "Orion is thrilled to be a Qlik technology partner. The integration of our EIIG platform enables Qlik users to see key data metrics such as quality score, value score, and trust score right in their Qlik apps. Users can dive into the EIIG platform to see data lineage and get more insight by leveraging metadata analytics such as impact analysis. EIIG's Qlik extension also delivers augmented data quality and allows users to tag all PII data assets right in Qlik apps for data privacy and regulatory compliance," said Niu Bai, Head of Global Business Development at Orion Governance.

The demand for data and artificial intelligence (AI) continues to accelerate. An executive survey on big data and AI found that 99 per cent of firms have now made investments in these critical areas. A survey by EDBI and Kearney of the ASEAN countries including Singapore, Malaysia, Indonesia, Thailand, Vietnam, and the Philippines found that if applied and executed well, AI could add $1 trillion to the region's GDP by 2030. However, despite the rush to embed data, analytics and AI into organisations' day-to-day operations, enterprises must realise that a radically different approach to data architecture is needed if they are to successfully put intelligence at the heart of their response to every business moment. Currently, just a fraction of data is properly used in analysis.

This is despite most business leaders predicting an upheaval in working practices due to the rapid onset of artificial intelligence (AI). With 35% of employees surveyed reporting they had changed jobs in the last 12 months because their employer wasn't offering enough upskilling and training opportunities, there is a stark need to better upskill workforces to support the workplace transition that is already underway. The report combines insights from expert interviews with surveys from over 1,200 global C-level executives and 6,000 employees. The findings, which were largely consistent across all geographies surveyed, reveal how the rapid growth in data usage is extending enterprise aspirations for its potential and, in turn, transforming working practices. The study found that business leaders and employees alike predict that data literacy – defined as the ability to read, work with, analyze and communicate with data – will be the most in-demand skill by 2030.

PHILADELPHIA, March 22, 2022 (GLOBE NEWSWIRE) -- Just over one in five employees believe their employer is preparing them for a more data-oriented and automated workplace (21%), according to new research from Qlik, a leader in data analytics. This is despite most business leaders predicting an upheaval in working practices due to the rapid onset of artificial intelligence (AI). With 35% of employees surveyed reporting they had changed jobs in the last 12 months because their employer wasn't offering enough upskilling and training opportunities, there is a stark need to better upskill workforces to support the workplace transition that is already underway. The report, Data Literacy: The Upskilling Evolution, was developed by Qlik in partnership with The Future Labs and combines insights from expert interviews with surveys from over 1,200 global C-level executives and 6,000 employees*. The findings, which were largely consistent across all geographies surveyed, reveal how the rapid growth in data usage is extending enterprise aspirations for its potential and, in turn, transforming working practices.

As AI transforms global workplaces, new research shows that data literacy will be the most in-demand skill by 2030. According to research from Qlik, a little over one in five employees believe their employer is preparing them for a more data-oriented and automated workplace (21%). This is despite most business leaders predicting an upheaval in working practices due to the rapid onset of AI. The report, Data Literacy: The Upskilling Evolution, found that 35% of employees say they had changed jobs in the last 12 months because their employer wasn't offering enough upskilling and training opportunities. Developed by Qlik in partnership with The Future Labs, the report combines insights from expert interviews with surveys from over 1,200 global C-level executives and 6,000 employees.

Qlik has deepened its work with Amazon Web Services with the release of an advanced analytics connector for Amazon SageMaker and integration with Amazon SageMaker Autopilot. These integrations increase the breadth of advanced analytics capabilities already available in Qlik Cloud, providing seamless integration to Amazon's advanced machine learning capabilities all via Qlik's Active Intelligence Platform. "Advanced machine learning capabilities to drive more predictive and prescriptive analytics is an important part of our vision for Active Intelligence, where businesses can seize every business moment," says Qlik chief product officer, James Fisher. "Now users of Amazon SageMaker can take advantage of their offerings directly in our SaaS platform, opening up even more opportunities," he says. "This capability supplements what is available today via Qlik AutoML, and illustrates our ongoing commitment to being a fully open, independent platform for data."

Bangalore – Qlik deepened its work with Amazon Web Services (AWS) today with the release of an advanced analytics connector for Amazon SageMaker and integration with Amazon SageMaker Autopilot. These integrations increase the breadth of advanced analytics capabilities already available in Qlik Cloud, providing seamless integration to Amazon's advanced machine learning capabilities all via Qlik's Active Intelligence Platform . "Advanced machine learning capabilities to drive more predictive and prescriptive analytics is an important part of our vision for Active Intelligence, where businesses can seize every business moment. Now users of Amazon SageMaker can take advantage of their offerings directly in our SaaS platform, opening up even more opportunities," said James Fisher, Chief Product Officer at Qlik. "This capability supplements what is available today via Qlik AutoML, and illustrates our ongoing commitment to being a fully open, independent platform for data." The new Amazon SageMaker connector is part of Qlik's Advanced Analytics Integration strategy, offering native, engine-level integrations built directly into Qlik's cloud analytics. It enables direct data exchange between Qlik's Analytics Engine and Amazon SageMaker to deliver a set of predictive data and updated calculations in real time as the user interacts with the data.

In this latest Data Science Central webinar, taking advantage of the newest innovations across the business intelligence and analytics landscape is critical to stay ahead of the competition and drive real value from your data. AI, machine learning, and cloud are all raising the bar, and you can position yourself to take advantage of these new capabilities now and in the future. Join Wayne Eckerson from the Eckerson Group along with Chris Mabardy and Denise LaForgia from Qlik as they explore how the BI market is evolving, and the key technologies that will unlock the value of your data for everyone. Topics discussed will include: - The importance of augmented analytics that leverage AI and natural language processing - How automated machine learning can bring the power of data science to analytics teams - Why the rise of cloud analytics is critical to harnessing BI innovation Register today to get our insights on the evolving BI market and future proofing your BI investment.

According to Gartner, NLP turns "text or audio speech into encoded, structured information, based on an appropriate ontology." Augmented analytics uses two subtypes of NLP, which are natural language understanding (NLU) and natural language generation (NLG). NLU enables the platform to understand a user's query while NLG "narrates" data visuals. NLU applies to text and audio. However, typed queries are more common than voice queries today for several reasons, most notably because the former is an easier problem to solve.

During the progress of any data science project, most data scientists tend to utilize tools and gadgets that would help them reach their goals faster and more efficiently. They use these tools to speed up routine tasks to save their energy and brain-power to find solutions for the current problem they are trying to solve. Because of this desire to speed up a project's workflow, there are so many data science tools out there that you can choose from, whichever suits the task at hand. And believe me, when I say this, there are hundreds of tools you can choose to finish your project; at the end of the project, you will discover that you used multiple of these tools to finish one project. Since any data science project consists of different steps, from gathering and collecting data to clean it, analyzing, and visualizing it, there are tools designed and developed for each of these steps. Tools to automatically collect data for you from all over the web, or tools to visualize your data and help you tell the story hidden within, or tools to help you clean your data and use the most relevant part of it in your analysis.