Over the past year, enterprise digital transformation efforts have accelerated dramatically with a substantial focus on not only how data is managed and stored, but how data is leveraged to deliver business insights.
DataOps continues to gain a foothold at organizations hungry for speed, agility, and innovation. The adoption of machine learning and complementary technologies, such as knowledge graphs, is on the rise.
There is an increasing emphasis on edge data and analytics in concert with IoT initiatives. All the while, the deployment of cloud platforms and services is ever expanding.
Looking toward 2022, DBTA gathered leading experts such as Jay Yu, vice president of product and innovation, TigerGraph; Anais Dotis-Georgiou, developer advocate, InfluxData; and Nicolas Kruchten, VP Product Plotly, for a special roundtable webinar to dive into the top trends in data science and engineering.
According to Gartner, “By 2025, graph technologies will be used in 80% of data and analytics innovations, up from 10% in 2021, facilitating rapid decision making across the enterprise,” Yu noted.
Graph naturally connects data together in a simple and efficient way that other big data technology cannot do, Yu said. Graph is a natural, adaptable model for transforming data into knowledge and insights.
Yu predicted 2022 will see the rise of graph data science. This would be the natural merging of data plus learning where relationships are fundamental.
Krutchen believes that low-code analytical apps built by data scientists will become a 2022 trend. To unlock the value of AI, Data Science has to be a team sport. That’s what Dash Enterprise by Plotly is for.
Fortune 500 companies are using Dash Enterprise to connect end-users to AI through their existing workflows. Low-code Dash app development supercharge s developer productivity, Krutchen said.
InfluxDB 2.0 is a purpose built time series database visualization, query and task engine, Dotis-Georgiou explained. She sees 2022 bringing inter-enterprise models and strategic data alliances, mapping automation, consolidated data models for IoT, and more.
InfluxData is preparing for the future by offering its own solutions such as Prophet, which provides forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data.
Zeppelin Notebooks combined with InfluxData offers a completely open web-based notebook that enables interactive data analytics, noted Dotis-Georgiou.
An archived on-demand replay of this webinar is available here.