In an age where businesses are competing ever so aggressively to gain new customers, retain existing customers, and improve operational efficiency, not having a data warehouse pushes companies ever so close to losing competitiveness. With the advent of cloud computing and the rise of cloud-native, serverless, data warehouses; it is about time that companies start to take data warehousing seriously. Read here for a more in-depth view of why we feel so.
Aging Data Warehousing Infrastructure
Data warehousing has traditionally been an IT function, carefully curated, and managed. It was necessary to ensure the demands of critical resources are met before addressing less pressing needs and more importantly to ensure governance. But how is this infrastructure supporting the demands of growing data science and analytics teams who are tasked with finding avenues to improve efficiency and to grow the business? It is often the case that running on aging DW infrastructure stifles innovation when the demand for data is increasing at an exponential rate.
A Massive Backlog of BI Projects
Often the case in a traditional data warehousing setup. However, what is the cost of critical resources spending hours every week on workaround solutions built-in spreadsheets? Does it have to be the case in 2019? – NO.
Custom Scripts to do ETL
Developers love this, and business users hate it. Why? Because they don’t scale, they are not reliable, and when they break, the fixes may not happen on-time. If your developers are writing custom scripts, then you are certainly taking their time away from building innovative solutions.
Multiple Applications Supporting Business Operations
Often the case these days with the increased usage of SaaS applications like Salesforce, Google Analytics, Freshdesk and marketing platforms like Klaviyo, Hubspot, and others. This trend is only moving in one direction and that is upwards. More and more best of breed applications are being leveraged in place of large monolithic software packages. Quite a few of these applications are replaced more frequently now that they did earlier.
Rapid Company Growth
A company’s growth intrinsically increases the demands on resource time to deliver more to sustain growth while hiring catches up and new resources ramp up. Ensuring your resources are spending time on activities that directly contribute to growth is vital to maintain this growth and to prevent resource burnout.
Increasing Volume and Variety of Data
Relational databases, document databases, SaaS application, webhooks, files, REST APIs, SOAP APIs, and the varied implementations of each of technologies add a lot of variety and complexity to the tech stack supporting an organization. Handling this complexity is best left to experts who specialize in this area rather than thrusting this role on to an already burdened data engineering and data science teams.
Running Resource-Intensive Queries on Production Databases
You need to stop now if this is happening.
Manual or Spreadsheet-Based Reporting
Even the creators of excel may not have envisioned the outsized role this software plays in all aspects of the business. Is it convenient, yes! Are you losing out because of this? – quite possibly.
Delays in Getting Visibility into Business Metrics
Do your executives have access to business KPIs on their fingertips or are someone compiling spreadsheets and sharing them via email regularly? Is an important decision delayed as a result?
Increasing Demand for Predictive Analytics
It is no imagination when someone says Data science is in vogue these days, going by the number of companies assembling these resources to tackle critical business challenges. What fun is it if they are spending most of their time extracting data?
Talented yet Understaffed Business Intelligence, Analysts, or Data Science Teams
You put together a great team, but you are still unhappy with their delivery. A big reason here could be that their time is being unproductively spent on data wrangling instead of on data modeling and analysis.
Cloud Data Pipeline
A cloud data pipeline is an ally for analysts. It reduces the dependency on IT and technology teams for analysts, provides an easy to use, configurable interface to setup ETL jobs, and makes data available in the data warehouse without analysts needing to write any code or maintaining any infrastructure. Daton is a cloud data pipeline by Saras Analytics and is designed to make life easy for developers and analysts alike.
