Transforming Big Data Initiatives Into AI Insights: Board Directors And CEO’s Must Improve Their Digital Literacy
This blog focuses on strategies to transform enterprise data into strategic real-time AI driven insights, and outlines the requirements for Board Directors, CEOs and leadership teams to increase their data literacy management skills.
There have been many definitions on what is big data over the years, ranging from Gartner describing big data analytics as high volume, high velocity and high variety assets that aid in decision making. Other academic experts, like Ackoff has focused on the conversion of data into cognitive value or wisdom, where an organization focuses first on data, then information, then into knowledge and then into meaningful insights or wisdom.
According to Wiki Encyclopedia, big data is a field that treats ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software.
According to Technavio, the big data market will witness an incremental growth of over USD $247 Billion at almost 18% CAGR during 2021-2025. This incredible growth has been driven by the acceleration of adopting consumer based applications resulting in huge volumes of both structured and unstructured data.
With the data tsunami and growing adoption of Industry 4.0 digital transformation programs, big data analytics to derive more wisdom (aka insights) is increasingly a core competency for critical operational and managerial decision making practices.
Technology architectures of moving all corporate data to the cloud for end users to easily access and distribute data access across multiple machines, while using the pooled power and storage to surmount monolithic bottlenecks is a top CIO priority globally.
I remember when Hadoop was released in 2006 by Apache, co-founded by Doug Cutting and Mike Cafarell as a project, originally based on Google’s Google File System Whitepaper. Amazon is even based on the Apache Hadoop, a Java based software programming framework that supports the processing of large data sets in a distributed computing environment.
Fast forward to today and there are hundreds of leading big data platforms to choose from, including market leaders like: Databricks Lakehouse Platform, GoodData, Google BigQuery and Google Cloud, Cloudera, Hortonworks Data Platform, IBM SPSS, Microsoft SQL Azure Server Platform, Pentaho, Snowflake, etc.
Top 5 Challenges of Big Data for Leaders to Take Seriously
1. Access to Knowledgeable Professionals – Big Data management is complex business and requires skilled expertise, ranging from: data software engineers, data mining analysts, data visualization experts, data scientists, communication and change management expertise and most importantly, business process experts that understand the process linkages and metric outputs to operate the business. There are risks in every large multi-national in data stewardship and in middle management and emerging companies, the risks are even higher. Do a quick survey of your board of directors, your CEOs and executive teams, and ask these two questions: Is anyone certified in data management? Then go to your next leadership level, VPs, and Directors and ask the same question. If you want to become more alarmed, drill down further and ask how many of the executive team are trained on AI and Machine Learning and Advanced Analytics and repeat this question at the second tier level. I have been advocating more accelerated digital literacy training for all management and certifications to modernize more efficiently, and I must admit in every organization I speak to these days on my zoom calls, data lineage and data accessibility and data stewardship guard rail challenges persist everywhere.
2. Ensure Actionable Insights – It’s easy to get lost in the data wrangling world and whipping up Power BI or Tableau visualizations, etc.
