Ever wondered why tech giants spend billions to acquire other companies? Discover how the Top acquisitions big tech companies made are changing the way businesses use data, build AI, and stay ahead of the competition.

Big Tech companies are not just acquiring other businesses or their products. They are acquiring the data, expertise, and capabilities that will enable them to win the competition in AI and digitalization. But which deals made the biggest difference? In this Business Fortune article, we explore the Top acquisitions big tech companies made to strengthen their data capabilities, from LinkedIn and GitHub to Tableau and Looker. This is how one can understand that data is one of the key components of the technology industry and its impact upon services that are used by the people on a daily basis.

What Do Big Tech Companies Need From Technology?

Data enables organizations to understand their customers, identify patterns and trends, build up their services and make the right decisions. This is why in connection with the growing usage of AI, it is crucial to have proper data and people who can analyze it.Creating all these things from scratch would take many years. An alternative way to acquire all these things is to buy another company.

  1. Microsoft Acquired LinkedIn for $26.2 Billion

LinkedIn was purchased by Microsoft in 2016 at a cost of around $26.2 billion. LinkedIn had an extensive network which had details on professions, skills, organizations, recruitment and business connections.

With the acquisition, Microsoft got the chance to use professional networking with its products like Office and its enterprise solutions. Businesses would be able to use professional expertise while recruiting employees and building relations. Microsoft gained an established professional ecosystem that could support its wider business strategy. It remains a strong example of how big data acquisitions can create value through networks and business information.

  1. IBM Acquired The Weather Company's Business for About $2 Billion

In 2015, IBM decided to buy the B2B, mobile, and cloud operations of The Weather Company for approximately $2 billion. Weather Channel television network was not included in the transaction.

The weather data would help companies in planning their operations as well as dealing with any unexpected changes. Airlines would benefit from weather data by planning for disruptions, retailers would be able to predict demand changes, and energy firms would know more about weather requirements.

IBM got hold of the weather forecasting technology and data which would be useful for the firm's business services. It became clear that not all data valuable for companies comes from internet usage.

  1. Salesforce Acquired Tableau for $15.7 Billion

In 2019, Salesforce bought Tableau for about $15.7 billion in an all-stock deal. Tableau offers insight into complex data using graphs, dashboards, and visualized reports.

Companies collect huge amounts of data, but they struggle to find a solution in it. Using Tableau, companies could easily analyze their data and look for patterns.

This deal strengthened Salesforce's data analytics capacity alongside its customer relationship management offerings. Companies were able to learn more about their sales performance, customer behavior, and changes in the market.

  1. Google Acquired Looker for $2.6 Billion

In 2019, Google bought Looker for $2.6 billion, and the deal was closed in 2020. Looker is a business intelligence company that provides software to analyze data from various sources. This acquisition made Google Cloud services more powerful as they became capable of providing analytic functions for enterprises.

Companies could use these functions to analyze sales data, performance of websites, as well as customer behavior in one analysis environment. Looker was an asset for Google that provided the organization with the means to transform random data into valuable information. It serves as a good example of data management acquisition since it is aimed at improving the analysis of information and not its collection.

  1. Microsoft Acquired GitHub for $7.5 Billion

Microsoft made its decision to buy GitHub in 2018 for $7.5 billion of Microsoft stocks. GitHub is a platform which enables storing of code, sharing of projects and software collaboration. However, the significance of GitHub does not end at its platform. The company gains access to a large community of developers and to an already existing platform for software development.

Moreover, the acquisition was later linked to the implementation of Microsoft's AI strategy. An example is the launch of GitHub Copilot, which assists developers in their coding work. However, the access to code is still bound by the laws of usage, privacy and license. GitHub is an example of an acquisition that brings AI capabilities through software ecosystem and developers' expertise.

  1. Google Acquired DeepMind to Strengthen AI Research

Google purchased the UK artificial intelligence firm DeepMind in 2014. The terms of the deal were never publicly disclosed at the time.

DeepMind contributed machine learning research, technical expertise, and highly talented scientists, which resulted in breakthroughs like AlphaGo, the artificial intelligence program which was able to beat the world's best Go players.

This acquisition was different from the typical acquisition of customer databases in that it was mostly about securing the right talent and technology to develop advanced AI systems. In addition, this deal shows how AI acquisitions differ from data acquisitions. Data assists AI programs to learn, but talent, computation resources, and model design are just as important.

  1. Google Acquired Kaggle to Connect With Data Scientists

In 2017, Google bought Kaggle. It is a platform used by data scientists and machine learning practitioners for competing and exchanging knowledge using datasets. It allowed Google to get closer to a worldwide community of data experts. The users are able to use datasets, test theories, create models, and learn from others' work.

The example proves that there is more behind purchasing of a data company by a technology firm. The value of Kaggle is not limited to the resources it offers, but also includes the experts who solve data-related challenges on the platform. In this way, the connection helps google promote data science and machine learning skills.

  1. Amazon Acquired Twitch for $970 Million

The live streaming service, Twitch, was acquired by Amazon in 2014 for $970 million in cash. Twitch is an online streaming community for gamers, creators, and audience who communicate with live videos. The business gets its value from insights into viewing behavior, audience engagement, and content preferences, according to the privacy policy.

This deal helped Amazon in developing the digital entertainment industry. Audience insights also assist companies in making business value by recommending better advertisements and user experiences. Twitch is not exactly a company focused on managing the data. It, however, shows how an online platform can generate business value from its audience and their activities.

  1. Facebook Acquired WhatsApp for About $19 Billion

Facebook, or more accurately Meta now, made its acquisition of WhatsApp in 2014. At the time the transaction was announced, the initial valuation of the deal was around $19 billion, although the actual amount depended on the price of Facebook's shares. With this acquisition, WhatsApp gave Facebook an important entry into messaging worldwide and an opportunity to use an already existing user network. Additionally, it created possibilities to create a business messaging solution.

However, it is not possible to obtain full access to messages through the acquisition of a messaging service. WhatsApp utilizes end-to-end encrypted personal messages and calls to protect the content. This is just another example of how valuable it is to have user bases and widespread use of technology. At the same time, it explains why privacy concerns should play a key role in data strategy for big techs.

  1. Microsoft Acquired Nuance Communications for $19.7 Billion

In 2022, Microsoft acquired the company called Nuance Communications. They paid $19.7 billion for the acquisition in cash and took up all their debt obligations. The main area of their interest is developing software in speech recognition, conversational artificial intelligence, and health care that will transcribe voice to text.

It enhanced Microsoft's AI in the field of healthcare, which is unique and needs special language and knowledge. For instance, speech recognition tools can make it easier for healthcare practitioners to document their visit with patients.

With this deal, Microsoft gained not only AI technologies but also industry experience and customer relationships. This is a perfect example of how acquisition of specialized firms can help technology firms create useful AI services.

What These Deals Reveal About Big Tech Data Strategies

All these acquisitions are based on a similar concept, where data is seen as being worth more once a company knows how to use it. Some deals provide professional contacts, weather forecasts, software data bases, or even predictions about consumer behavior. The best acquisitions will be those with more than one capability.

Microsoft can combine cloud computing, artificial intelligence, and enterprise software capabilities. Google can combine cloud computing, analytics, and artificial intelligence research capabilities. Salesforce can combine customer data and business intelligence capabilities.

Still, acquisitions are not always guaranteed to be successful. Combining different systems will be challenging for any company. Privacy concerns, security issues, data quality, competition, and even maintenance costs will have to be considered.

The challenging issue here is the contribution made by an acquired company toward improving customers' ability to address their problems. Having more data does not help if the data is old, disorganized, and unusable.

What Comes Next?

Big data acquisitions in the future will most likely be focused on companies that can help big tech companies to develop or upgrade their AI technology. Sectors such as data infrastructure, cloud analytics, cybersecurity, and custom datasets are expected to be attractive. With the expansion of AI, companies will require quality information, secure data, and solutions that provide accurate information.

But every company will not opt for acquisitions. There might be companies that create their technology or form partnerships. The approach of such data by the big tech firms has clearly shown that success depends on the proper use of data. With technology, human beings and data at work, businesses will be able to make more effective products and better decisions.