Analytics today comes in a lot of shapes and sizes. We consider the entire flow in designing our industry-leading platform.
You’re drowning in it. How well you understand what it’s telling you determines whether your business is successful or fails. How do you get the understanding you need to win in the market?
“Analytics” is everywhere. Most companies have relied on the canned analytics in their individual applications (Salesforce, ServiceNow, Splunk, PowerBI, etc) plus spreadsheets to try to glean insights into what’s going on to better inform decision making.
But these canned analytics are siloed and only consider data from a specific application. Salesforce analytics can’t use Splunk data to generate insights. What’s needed?
Numerous solutions, like Tableau, have arisen to give an overall view of what’s going on across your data sets. Until recently, most took a simplistic approach of looking at certain types of data from certain sources and doing some partial processing to improve insights.
This limited approach was an improvement on canned analytics but still left a huge amount of work to the user. What was missing was baking in of…
Newer analytics solutions have begun to incorporate some level of artificial intelligence and machine learning to increase automation and accuracy of insights. This has truly transformed how organizations manage and monetize their data.
But these solutions remain piecemeal and still require significant data science work to generate valuable insights. What do organizations that don’t have large data science teams need to generate insights?
A true modern analytics platform starts with data and automatically delivers all the insights an organization needs to make fully-informed decision making.
To fully identify and address businesses needs, this platform must:
- Incorporate all data types from all sources
- Stitch it together into a single pool with common categories and formats
- Use built-in data science to extract patterns, behaviors, and algorithms
- Leverage artificial intelligence and machine learning to adapt analytics to changing data types and user needs
- Present insights via intuitive dashboards constructed from plain-English queries
…all without the intervention of data scientists or IT teams!
That’s Tinosys TrueInsights, a complete analytics platform that acts as your data science team in a box. We help organizations of all sizes finally reach their true potential through full-informed decisions based on data from every corner of their business.
Our simple yet powerful approach has 4 steps
Consolidate data of all types from all sources
Stitch all data together into one common structure (not just a data lake)
Analyze consolidated data, agnostic of type or source, to identify relationships, trends, and patterns and extract predictive and prescriptive insights.
Present these insights in an intuitive way that’s most useful for a business to use
Tinosys ingests data, either through manual upload to our portal or via our connectors to your data sources, then generates metadata for each dataset. After that, Tinosys classifies the data into standard types (Identity, entity, dimension, metric, date, etc.) and stores it and metadata in our data lake.
While analytics vendors offer cheap storage and tools to manage and structure the data once it’s loaded, Tinosys is the only vendor to scan and structure data before putting it into our data lakes, dramatically improving speed, accuracy, and automation.
Unlike all other analytics vendors, for data in the data lake, Tinosys AI models automatically scrape the data and metadata to find commonality to consolidate into one single data and metadata set, without the need for a data scientist to pre-process it for analytics.
Tinosys AI models convert all non-categorical data into categorical data, example classification, and hierarchy, then store it in query-able, common data fields.
Most vendors provide statistical analytics and query language for customers to manually build their analytics, metrics, and trends. Tinosys pulls possible metrics, categories, and hierarchy for the customer, significantly reducing or eliminating the complex data science process.
And while other tools give you analytics based on what you ask for, Tinosys also reveals insights that might have been in your blind spot, keeping you fully aware of what’s going on in your business through one intuitive tool.
Tinosys conversational analytics builds SQL queries automatically based on customers’ natural language questions through a guided process. Results are presented in automated dashboards with descriptions, charts and tables.
This greatly simplifies and accelerates access to accurate customer insights and predictive analytics at significantly lower cost.
Interested? Skeptical? Please check our Product Demo for more details on our features and capabilities.
We look forward to helping you achieve your customer satisfaction goals.