Into the Unknown: 8 BI & Data Trends That Are Shaping 2021
The economic uncertainty caused by the COVID-19 pandemic proved that analytics is more than a competitive advantage: It is the most critical component of a competitive, highly successful, and future-proof business.
Analytically mature organizations adapted to 2020’s rapidly changing conditions by using data to effectively adjust their strategies and quickly pivot to take advantage of new opportunities as they presented themselves.
For example, the marketing team at Migo, a cloud-based platform that enables B2C companies in emerging markets to offer credit to their customers, was in full growth mode at the start of 2020. But the challenges brought on by the COVID-19 pandemic required the marketing team to quickly shift gears and focus on customer retention and loan recovery.
“Because we had immediate access to all of our data, could run any analysis without the assistance of the BI team, and knew the data was accurate, we were able to pivot and relaunch our entire marketing strategy in just 30 days,” shares Migo’s Head of Marketing, Alex Harvey. The result? A 47% increase in campaign response rates.
As we prepare to enter a new year of great unknowns, data — and the underlying tactics, tools, and technologies that enable companies to harness its full value — remains the answer. A new generation of data analytics is upon us, and it’s real-time, scalable, and accessible to every level of technical expertise.
The Death of
Imagine you’re a marketing executive, just for a moment:
You spent weeks preparing for the quarterly board meeting, and you arrive armed with a flashy new dashboard your BI team built for you. But during the meeting, one of the board members asks a question that isn’t answered on your dashboard. You have no choice but to tell everyone they’ll have to wait at least a week for an answer so your BI team can update the dashboard with this new analysis. The energy in the room quickly evaporates, and you leave the meeting feeling frustrated, powerless, and a little embarrassed.
Given this scenario, it’s easy to see why the novelty of visualizations and dashboards from the last two decades has worn off for line of business teams.
Point-and-click dashboards were great when being “data-driven” meant reporting out on a limited, predefined set of business metrics. At best, these traditional dashboards offer surface-level reporting on what is already known, and worse, leave their consumers without the ability to ask follow up questions without going back to the BI team for help.
But needs and expectations have evolved. Today’s business teams require the ability to dig directly into data — often at the most granular level — to make critical decisions on-demand. As a result, BI solutions and their users are moving away from canned, surface-level dashboards toward dynamic, in-context analyses that surface real-time, highly relevant insights.
In short, the death of the dashboard as we know it is giving rise to BI and cloud data exploration tools that empower non-technical business experts to go beyond the dashboard to independently find answers to their most pressing questions –– without having to wait on data and BI teams.
Sigma is like I’m working in a spreadsheet, but all the data is live. I can explore all of our data at the lowest level of detail and do ad hoc analyses in real-time without any limitations. I love being able to join my own datasets based on unique customer identifiers and build on dashboards without having to go back to Joseph [BI] and re-work things.”
Marketing Lead at Migo
The Rise of Cloud Data Exploration
Research shows 81% of companies agree that data should be at the heart of all decision making — that’s why the BI market is a nearly $30 billion market. But while modern data integration tools paired with a cloud data platform solve the first part of this goal by preparing data for analysis and transforming it into a usable asset, 63% of decision-makers still report that they’re unable to get the answers they need in the required timeframe.
of companies agree that data should be at the heart of all decision making
Business Intelligence Market value (projected to reach $54.76 Billion by 2026)
of decision-makers still report that they’re unable to get the answers they need in the required timeframe
Today’s business teams need real-time access to the massive amounts of data pouring in across channels to make the daily, on-demand micro-decisions that add up and impact the organization’s macro, long-term success. The bottom line: Static reports and surface-level dashboards simply won’t cut it for current data-driven decision makers looking to beat the competition.
Companies have fallen short of enabling organization-wide data-driven decision-making for three primary reasons:
- InfrastructureMost of today’s analytic systems and tools were designed for on-premise warehouses and have been retrofitted as SaaS tools. They often require data to be extracted for preparation and heavily modeled by the BI team before it can be used by domain experts. This not only prevents business teams from getting a complete, up-to-the-minute picture of their data, but it also makes it impossible for them to analyze it at its lowest level of detail. What’s more, these “cloud” solutions are still known to choke on large datasets.
- AccessMost analytic solutions require the use of SQL or proprietary code to drill into data, which prevents non-technical business users from getting their hands on the data they need to make timely decisions. These individuals can’t afford to wait at the back of the BI team’s request queue and are forced to access the data the only way they know how: by extracting it to spreadsheets. This creates its own set of issues including stale data, data silos, scale limitations, and worst of all, governance and security risks.
- DashboardsDomain experts are often limited to view-only metrics in surface-level, static dashboards, which prevent them from performing more in-depth analyses. If they have follow-up questions about the data, they must go back to their data or BI team — a cycle that can take days, if not weeks, to finally obtain useful insights. (See Trend #1).
What is the modern cloud data analytics stack?
The modern cloud data analytics stack consists of three layered technologies and cloud-based services that collect, store, and analyze data. Together, these tools allow organizations to unlock the full value of their data and fuel smarter decision making for all.
THE DATA pipeline
Data must be collected and integrated across applications, databases, files, and more so it can be easily accessed, modeled, and holistically analyzed. The modern data pipeline (e.g., Fivetran) automatically connects and normalizes data from across sources in real-time, preparing it for storage and querying using analysis-ready schemas. Plus, it’s true self-serve, as, with only a few clicks and a 14-day free trial, anyone can start pulling data into their data platform.
THE Data platform
Most companies wrestle with disparate data: some is structured, some semi- or unstructured, and there is no single source of truth from which they can reliably consolidate data and correlate analytics. Cloud data platforms serve as a centralized repository for all of the data In an organization. The Snowflake Data Cloud provides elastic infrastructure, unlimited scale, cost-effective risk mitigation, security management, and other cloud-specific benefits traditional on-prem warehouses do not.
Cloud data exploration
To maximize the value of the data inside the warehouse and enable data-driven decision-making, companies must empower employees of all technical abilities to independently interact with data at cloud speed and scale. Cloud-native BI solutions (like Sigma) give everyone the ability to directly query live data from the Data Cloud, down to row-level detail — no manual SQL or proprietary coding required — while maintaining strict data governance. Teams can create visualizations, join data sources on the fly, unravel JSON, do rapid what-if analysis, and more via user interfaces that resemble tools they already know and love, like spreadsheets. In turn, BI experts can escape report factory hell and focus on the innovative and strategic projects they love.
Companies That Have Adopted a Modern Cloud Data Analytics Stack See Results Like:
Accelerated time to insight by building a key market report in 2 hours with Sigma vs. 2 months using previous tool.
Took back 50% of time spent filling ad hoc data requests to focus on more strategic and impactful data projects.
Cut customer acquisition cost by 50% by understanding the buyer journey and making data-driven marketing decision.
Still looking to complete your cloud data analytics stack?
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