How to Become Truly Data-Driven
Companies today don’t have the luxury of waiting to become data-driven while younger and more agile competitors are nipping at their heels. The pressure is on now to consolidate all data across the organization for a single view into operations, processes, and customer service.
But why is becoming data-driven such a headache?
It’s all too much
While the cloud always promised a new era of productivity (and it has delivered to a great extent), the reality is that its explosion in the 21st century is leading to a mini implosion. The average company uses 1,400 cloud services across 4.8 private and public clouds to run applications and services. In other words, enterprises are running too many public and private clouds, from too many vendors, each containing too many disparate workloads in silos, being measured by too many different tools.
This cloud sprawl and unchecked visibility into siloed operations is preventing analytics teams from doing their jobs efficiently and having the right data easily at their disposal. Luckily, enterprises can buck the trend of losing market share to their more agile competitors with a strategy that makes all of their data readable, accessible, and easy to integrate.
Eliminate the barriers with an adaptive analytics fabric
An adaptive analytics fabric enables enterprises to transform themselves into truly data-driven organizations. It removes the obstacles that prevent data consolidation and produces shared insights across the organization through a unified semantic layer, regardless of where the data is stored.
An adaptive analytics fabric translates and transforms proprietary and disparate data formats into one common, business-centric format and view of the data, so everyone in the organization speaks the same analytical language and gets the data they need, when they need it. Moreover, when conducting data analysis with BI and other analytics tools, users know that their analyses will yield consistent results with a single data source driving queries. Thus, business analysts and data scientists will benefit from:
- A single, unified, easily accessible view into disparate data systems
- Accelerated query results across BI tools, ML and AI
- Minimized business disruption during the process
A single view
Organizations have data in databases that span query languages from any number of SQL variations to MDX. Bringing together disparate datasets, each with different business logic and query semantics, across the enterprise is a recipe for disaster if analytics teams are going to perform analyses with multiple different tools.
Enterprises need the agility that stems from normalizing data across all clouds, systems and siloes with a common business logic, agnostic of BI and other analytics tools. A universal semantic layer and standard business logic over the existing infrastructure will transform data into business-ready formats that can be used by any business analyst or data scientist, with whatever analytics tool they choose. In turn, BI teams can also have instant self-service access to analyze and share this data without having to worry about its integrity, or learn new tools and systems to compare disparate data sets.
Accelerated query performance and agility
With those agile startups ready to chomp away at enterprises’ market share, even minutes lost can mean missed business opportunities. But with queries that can take hours or even days because of the sheer volume of raw data in an organization, this is easier said than done.
Shortening query times undoubtedly makes data consumers primed for better operational efficiency, and in turn, more wins. An adaptive analytics fabric accelerates queries for BI teams and data scientists by applying machine learning to generate acceleration structures that improve query times from 5x to 100x depending on the dataset.
Minimized business disruption
For the business analysts, data scientists and other top organizational data consumers, an adaptive analytics fabric minimizes disruption and downtime by enabling seamless data migration from on-premise to cloud platforms.
Even when a database is migrated from legacy, on-premise solutions to the public cloud, an adaptive analytics fabric ensures the user will retain access to the data with minimum downtime. Data is moved to the new source in the background, and the virtualization solution just changes its internal pointers to the data source.
How Can AtScale help?
In order to become truly data-driven, organizations must sweep away the obstacles to unifying data and optimizing queries across the enterprise, without disrupting daily operations in the process. An adaptive analytics fabric such as AtScale’s A3 seamlessly creates the shared data intellect business analysts and data scientists need to drive wiser, data-driven insights to take the most profitable actions now and well into the future. With an unprecedented and unified view into all data and business operations, organizations can keep pace with, or even surpass, even the most hungry and data-savvy startups.
For more on how an Adaptive Analytics Fabric can help your business become truly data-driven, download the full white paper.