Companies today generate and collect an astounding amount of data.
Spending on big data and business analytics (BDA) is forecast to exceed $215 billion in 2021, an increase of more than 10% from last year. Organizations worldwide have embraced the use of data and analytics to drive strategy. The benefits for companies that adopt business intelligence as a core component of the strategy see significant benefits:
- Nearly 80% of businesses that are data-driven are more likely to grow revenue
- Insight-driven companies are taking $1.8 trillion in revenue from companies that aren’t data-driven.
- Data-driven customers are growing more than 30% annually.
Data has the power to unlock business intelligence to fuel growth.
It’s the reason CEO surveys by Gartner, Deloitte, and PwC all showed similar results. Business leaders say they plan to make their biggest investments in digital capabilities and information technology in the coming year.
Despite the results and enthusiasm for big data, companies are using so little of what they already have. A Forrester Research study said that just 12% of the data companies have is used for analysis and less than 30% of companies say they can translate the data into action.
It begs the question: with so much data being collected, why is so little being used?
Diverse Sources and Data Sets
The average company today is collecting data from 400 different sources. More than a fifth of organizations are using 1,000 or more data sources. Aggregating all of this data and transforming it into a useful form is challenging even with automation.
The volume and quality of data vary from sources as well. Without robust and reliable systems to scrub data for accuracy and turn it into usable formats that allow for complex queries and analysis, data can quickly become unusable at best and provide inaccurate results at worst.
Today, business intelligence tools do a much better job of managing data from different sources, such as multiple data warehouses. BI tools and data visualization, however, still suffer from data siloes preventing the use of data layers.
The vast majority of data that is collected is unstructured. Text, video, server logs, social media, and other unstructured data create a wealth of untapped resources. Because unstructured data doesn’t adhere to standard data models, they are more difficult to interpret. Yet, the use of such data can deliver a more comprehensive picture.
For example, social media postings can indicate consumer sentiment about brands and products that can be vital to understanding trends. Yet, without a way to parse the data, it’s difficult to allow automation to interpret and analyze it.
As much as 80-90% of all data falls into the unstructured category according to the MIT Management Sloan School.
Complex Data Environments
Complex data environments add to the challenge. In today’s multi-cloud and hybrid-cloud environments, companies are still mixing on-prem data warehouses and cloud warehouses. Too often, data sits in unconnected siloes without the ability to quickly provide a single source of truth.
Nearly half of companies (45%) report their data efforts are stalled because of complex data environments.
While data lakes are helping with the consolidation of storage for structured and unstructured data, much of it still resides in an unusable form.
Making data-driven decisions part of a company’s culture means moving data beyond just the domain of IT and data analysts. It needs to be accessible at both the executive level and on the front lines as employees make decisions.
Without a cultural shift the prioritizes data analysis — and the right tools to make it useable — for front-line employees, digital transformation will not be effective.
Even in companies that invested in big data, only 52% of enterprises make the data available to the front-line workers. Just 14% of organizations report that data is broadly accessible to team members beyond the executive suite. 72% of C-level tech and business execs say they have yet to create a data-driven culture within their organization, according to a report in the Harvard Business Review.
Lack of Resources
At the same time as all this is going on, companies are also fighting a growing shortage of employees skilled in data analysis. The deployment of AI, machine learning, natural language processing, data engineering, and data visualization has created a huge worldwide demand for talent where demand far outstrips supply.
Data scientists need a diversity of skillsets:
- Cleaning and organizing data
- Collecting data sets
- Mining data for patterns
- Identify business opportunities
- Refining algorithms
- Building training sets
The shortage of skilled data scientists is only expected to increase in the future.
Make More Effective Use of Data
Hakkoda offers several options to help organizations overcome the challenges of extracting maximum value out of their data.
Don’t let a shortage of available talent stop you from optimizing your data. We provide on-demand and ala carte data specialists that allow you to scale up and down whenever you need. Whether you need help with data analytics, migration, architecture, engineering, governance, machine learning, or app development, we can help.
The only way to harness this staggering amount of data is to leverage the power of automation, AI, machine learning, and rich data applications. By automating data pipelines, you can shift from human to machine decisioning to create better data analysis.
No Code Apps
A key to embedding business intelligence throughout your organization is extending the accessibility of data beyond your BI teams and corporate suite. At Hakkoda, we create enterprise-grade apps that provide the same high-quality you need at dramatically lower costs than traditional app development. This makes data available to your entire team at minimal costs.
Snowflake Concierge Services
For companies investing in Snowflake, our concierge service can help with onboarding, governance, enablement, and training to accelerate and optimize the value of your cloud data platform. Snowflake decouples the storage and compute functions to maximize the storage of your data. This gives you mass storage capacity at an affordable rate while you only pay for compute time when it’s used.
To learn more about how you can extract more value from your data, contact the team at Hakkoda today.