In a recent DBTA roundtable webcast, I joined Couchbase’s Suphatra Rufo and Alluxio’s Ali LeClerc to unpack the top trends in today’s modern data architecture.

From AI and machine learning to data discovery and real-time analytics, a strong data architecture strategy is essential for achieving today’s data-driven enterprise goals. Triggered largely by the push to the cloud, our data architecture landscape has evolved significantly with the rise of many new technologies – which bring significant data access and management challenges.

The 4 Key Takeaways:

  1. The rapid growth of different database offerings, SAAS and social media applications has created significant market fragmentation. While relational databases still make up a significant share, we’ve seen a rise in popularity of many new database types such as NoSQL, Document Stores, Graph and Time Series databases.
  2. With the explosive growth of applications across industries, businesses rely on more and more data sources to make decisions. In marketing, the number of MarTech applications has spiked from 150 in 2011 to 7,040 in 2019, according to Chief Martec’s Marketing Technology Supergraphic. Furthermore, today’s marketers juggle an average of 16 data sources to track customers.
    marketing-technology-landscape-2019
  3. With companies using many different databases to solve different problems, enterprise data is getting locked away in specific applications. For instance, the ability to take Concur data to look at expenses in Tableau or PowerBI is a major conundrum without the right data connectors. Users may resort to downloading the data into a CVS file, a cumbersome and error-prone process. Read: Connecting Tableau to Concur-based Data
  4. While enterprise tools were traditionally built assuming SQL databases, many new databases are not SQL-capable or not compliant with standard SQL, such as NoSQL and popular Big Data sources like Apache Spark. Connectivity to these data sources can be limiting, which makes access to real-time data a challenge for businesses. Hence, the need for standards-based data connectors.

Collectively, these trends make gaining a holistic view of data for sound decision-making ever more complex. As such, data connectivity has become a strategic priority for small and large businesses to extract value from their greatest asset – data. Simplified access to data is crucial for driving performance, productivity and the bottom line.

Access the archive recording of this special webcast here for more insights.