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Overcoming Data Anxiety With A Data-To-Everything Approach
Making sense of data at a faster rate and in a smarter way is mission critical for all organisations. To optimise the entire data continuum, organisations need to implement a data-to-everything approach- invest in security analytics, automation and machine learning solutions and take control of data anxiety.
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Data is central to solving the world’s toughest problems. Whether through contact tracing for Covid or unwinding mass scale cybersecurity attacks, data is essential to providing the answers we need. Data complexity is amongst the leading challenges faced by C-suite across organisations. They are feeling the weight of keeping up with the ever-increasing volume of data and are often confronted with data anxiety due to poor data integrity and authenticity. Data is the foundation of insights, accurate data analytics and context is the only remedy to overcome data anxiety and ultimately accelerate innovation. Turning data into action is what we call a data–to-everything approach.
Here are some best practices organisations can take to turn data into measurable outcomes as well as overcome today’s threat landscape with a data-to-everything approach:
Accelerate performance-driven culture fueled by data: Every organisation needs a complete view of its data, and the ability to take immediate, insight-driven actions. Organisations need to consider investing in big data platforms that have the ability to pull and consolidate data across these various business units and present a holistic data set. This visibility across a single data set enables organisations to answer business-critical questions, focus on their customers and drive impact across businesses at a much faster rate while promoting a performance-driven culture fueled by data.
Use advanced analytics to prioritise incidents: Splunk’s State of Data Innovation report, recently found that established business leaders are 4.8 times more likely to make better data utilisation their top priority. While this affirms the importance of deriving insights from data, organisations are also faced with the challenge of keeping pace with the magnitude of data that is being generated every second while ensuring the authenticity or integrity of the data. Organisations need to streamline existing operations and leverage machine learning, automation and security analytics to lighten the data load.
Prepare in advance: The shift to a hybrid workplace model brought forward a complex threat landscape. As a best practice, businesses should implement technology solutions that go beyond monitoring and offer the ability to harness the power of data to investigate, analyse, and enable teams to sift through the noise and zero in on threats in record time. These solutions that use data models to remain agile, will help organisations prepare for evolving threats.
Focus on end-to-end integration: Organisations have been spending on multiple, best-of-breed tools to solve distinct problems associated with a digital landscape. However, instead, organisations need to invest in end-to-end integration that centralises data for analysis across the front end and orchestrates response on the trailing end, which helps ensure efficiency and accuracy. When assessing data strategy and next steps, consider broad and open platforms over deep and narrow solutions to reduce integration complexities that can potentially impact customer experience and the bottom line.
Making sense of data at a faster rate and in a smarter way is mission-critical for all organizations. According to Splunk’s State of Data Innovation report, results have shown that leading data innovators release twice as many products and increase employee productivity at twice the rate of organizations with less mature data strategies. To optimise the entire data continuum, organisations need to implement a data-to-everything approach, invest in security analytics, automation and machine learning solutions and take control of data anxiety.
Disclaimer: The views expressed in the article above are those of the authors' and do not necessarily represent or reflect the views of this publishing house. Unless otherwise noted, the author is writing in his/her personal capacity. They are not intended and should not be thought to represent official ideas, attitudes, or policies of any agency or institution.