Data is everywhere. It grows exponentially year by year, and it is our duty to keep up with its overwhelming volume and complexity. The thing is, we’re so focused on conquering our data that we often forget this battle to understand it has been one we’ve been fighting since the beginning of time. However, we’ve always overcome this and been able to synthesize and communicate our data findings throughout the years.
One of the most prevalent times in data evolution was the Information Explosion of 1961, in which there were tremendous economic and technological innovations due to a rapid increase in the production rate of new information. This sudden overload of information was overwhelming to the masses, which resulted in numerous companies being unable to make clear and accurate decisions due to the newfound complexity and volume of their data.
IBM’s contributions to developing digital data storing technology set the precedent for the standardized method of data storage for years to come. This method was later justified in 1996 when digital data storage was proven to be more cost-effective than storing information on paper, as stated in the 2003 IBM Systems Journal paper, “The Evolution of Storage Systems.”
“We are a business with a single mission – to help our customers solve their particular problems through the applications of data processing and other information handling equipment.” – Thomas Watson Jr., Former Chairman and CEO of IBM, 1970
IBM has long been a data leader throughout history. As a company, we have been entrusted with organizing data on a national scale, made revolutionary progress in data storing technology and have exponentially advanced trustworthy AI using aggregated structured and unstructured data from both internal and external sources.
Here are some of the key moments in IBM’s data and AI journey that showcase the evolutions of organizing, storing and leveraging data.
1928 Punch Card & U.S. Census:
1936 Social Security made possible by IBM:
1964 System/360:
1970 Relational database:
1971 World’s first floppy disc:
1981 The IBM 3380:
2021 2-nanometer chip:
1956 AI Before AI:
1997 Defeating the reigning chess champ:
2000 Deep Learning:
2022 The Mayflower Autonomous Ship Project:
The volume of data continues to grow exponentially, and organizations are faced with challenges due to managing the quality of their data, research states that,
Thus, why we have made efforts to help companies improve their business practices through data analysis. IBM’s data fabric approach prioritizes helping enterprises elevate the value of their data architecture, and through initiatives such as Customer 360 –which helps to reduce data quality issues in applications and optimizes business’ insights on customers.
Most recently IBM has acquired Databand.ai, the leading provider of data observability software that helps organizations fix issues with their data before it impacts their bottom-line –including errors, pipeline failures and inadequate quality.
This acquisition highlights our dedication to helping companies improve their businesses and highlights our continuous evolution of data and AI innovations.
Ultimately, as a data leader our goal is to help you organize, store and leverage data while deriving insights from complexity. Data is everywhere and will continue to grow exponentially, but the more quality data you have, the clearer you see.
IBM is here to provide the skills and solutions organizations need worldwide. To learn how to design an effective data strategy that helps you make the most of your data, read our new guide for data leaders, The Data Differentiator.
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