Breaking Down Data Silos and Transforming Business Intelligence

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The global market for business intelligence is forecast to reach nearly $30 billion by 2027. Advancements in artificial intelligence, machine learning, and predictive analytics are providing significant insights to many of the world’s most profitable enterprises. Intelligent automation and business process automation are accelerating the speed and accuracy of business systems and allowing companies to leverage their data in new and innovative ways.

However, there are challenges involved in data transformation. Becoming a data-driven organization requires breaking down data silos and embracing a holistic approach to data. This eBook will take a deep dive into the challenges, potential solutions, and recommendations for how to overcome problems associated with creating a successful business intelligence transformation.

Common challenges with breaking down silos and transforming BI
Why traditional approaches aren’t working
The importance of eliminating data silos and transforming BI
Potential solutions and alternatives
Answering BI questions and our recommendations
How to find the best provider to help you implement the best solution
KASH Tech’s four-phase process to produce strategic solutions

The sheer volume of data being collected today is enormous. Yet nearly 97% of the data gathered goes unused. Why? It’s often locked away in software and data silos and inaccessible broadly across the organization. Much of the data is unstructured, which may not fit neatly into legacy business intelligence systems. Data sources and data warehouses may not be configured properly.

These are just a few of the reasons companies have challenges when implementing BI transformation.

Common Challenges with Breaking Down Silos and Transforming BI

Here are some of the most common questions organizations ask when trying to overcome the challenges associated with breaking down silos and transforming business intelligence:

How can digital transformation help my business?
How do I bring various sources of data together to support our analytics?
How do you transform the business into a data-driven organization?
What does data transformation mean?
How do I diagnose and correct data inconsistencies and errors?
What are the best methods to eliminate data silos in our business?
What is data virtualization versus a data warehouse to make data more accessible?
How can the cloud help me with my information management challenges?

These are the right questions to ask. The answers can help you build the right solution for your business. However, traditional approaches to overcoming these challenges are generally falling short. Studies from McKinsey, Boston Consulting, KPMG, and Bain & Company all report that the risk of failure in digital transformation falls somewhere between 70% and 95%. Companies can spend a significant amount of time and money trying to overcome these challenges without ever achieving the results they need.

We’ll discuss alternatives and solutions that can help, but first, let’s examine why traditional approaches aren’t solving the problem.

Why Traditional Approaches Aren’t Working

Over time, companies have built legacy solutions. In most cases, this means bolting on new hardware and software to existing systems. Over time, this can create significant technical debt that makes it difficult to bring all of the data together in a comprehensive manner.

Outdated Process

For example, enterprises may still be using outdated processes such as an Extract, Transform, Lift (ETL) approach based on batches rather than real-time information processing. Batch processing will move the data to where it’s needed, but it’s cumbersome and delays the process.

New Data Silos

Besides existing data silos, businesses often create new data silos in response to operational demands or as a quick way to address analytics and reporting requirements. They may add new software or reporting workloads that only add to the problem. While addressing business-driven demands, they are failing to adhere to a strategic approach to business intelligence.

The Wrong Analytics Platform

Enterprises may be using the wrong data analytics platform that isn’t well suited for today’s data integration needs. Systems may not be scalable or sustainable.

No Single Source of Truth

Often, disparate systems are in place across an organization, limiting the scope of business intelligence. Platforms only have access to certain data sets, preventing analysis from having the complete picture. These data silos undermine trust.

Lack of Consistent Data Governance

Because data is often analyzed for specific or immediate needs, appropriate data modeling to accommodate a holistic analytics platform may not be considered. Data integration rules and business rules can get lost, leading to data governance issues.

Relying on Spreadsheets

Even with solid data sources and strong governance, many companies are still relying on spreadsheets rather than using data sources directly. This only adds to the number of data sources, which can quickly become outdated or out of sync.

The bottom line is that all of these traditional approaches create more data silos and more complexity, and engender less trust in the data itself.

The Importance of Eliminating Data Silos and Transforming Your BI

Failing to solve these challenges can impair even the most data-driven companies.

Without a single source of truth, for example, different people can come up with significantly different results. Managers might come to meetings with completely different insights gleaned from multiple sources of data or variants of the same data. In some cases, insights and strategies may conflict.

Even if the data is accurate, it may not be complete. This can lead to making poor business decisions. In the end, users may lose trust in the data rendering a company’s BI transformation unsuccessful.

Failing to overcome these challenges also contributes to:

Additional costs
Wasted employee time
Lack of accountability
Increased complexity
Animosity and finger-pointing

When systems break down like this, decision-makers lose sight of the underlying data insights and run the business on gut instinct instead of data.

Potential Solutions and Alternatives

There are multiple approaches to solving these challenges, including using in-house resources to solve the problem.

Solve the Challenges In-House

Tying up employees to create a holistic, enterprise-level solution may also create additional problems. Employees don’t have the time to find a solution and implement it themselves. Even experienced IT teams may not have the breadth of experience — or availability — needed to implement such an enterprise solution.

Rely on Software Vendors or Cloud Service Providers

While it would be great to pull a product off the shelf and deploy it, it doesn’t work that way. Every company has different data sources, systems, and process that requires custom solutions. Software vendors will approach businesses to buy more software to fix the issues, but they are locked into their product offerings and rarely take a holistic approach.

Cloud service providers (CSPs) will likely be part of any digital transformation, but each CSP has its pros and cons. Different providers work better and more efficiently at different aspects of data storage, data virtualization, and data processing. The best solution typically does not lie with any one CSP.

Use Consulting Companies

Consulting companies may help create a strategy, but do not implement it. Others will implement technology but do not drive a strategy to custom-fit a solution to business needs. They may rely on best-of-breed technology instead of a best-of-fit approach. With best of fit, the consulting company takes responsibility for the strategy and builds it to fit the needs of the people, processes, and technology using best-fit solutions.

What Do Industry Experts Say?

Industry experts will tell you that any of the solutions will have advantages and disadvantages but are all viable depending on your pain threshold and budgetary constraints.

There’s an old saying that applies here. You can have speed, quality, or low cost. You can have any two, but you can’t have all three. Delivering high-quality solutions requires time and investment.

Each party that provides a solution will have its own biases. Buyers need to understand any provider’s strengths, weaknesses, expertise, and bias.

Answering BI Questions and Our Recommendations

Avoid any company that has a cookie-cutter solution that’s plug-and-play. Eliminating data silos and transforming business intelligence requires a considered analysis of your current infrastructure and processes to determine a custom, best-fit solution.

It takes careful analysis and expertise to craft the right solution for your business.

Earlier, we posed several questions that companies undergoing digital transformation are asking. In this section, we’ll provide answers along with our recommendations.

How Can Digital Transformation Help my Business?

For each type of business, digital transformation will look slightly different. Digital transformation will help accelerate the creation and integration of data as well as the delivery of actionable BI to your team.

Solutions for overcoming challenges should focus on:

Eliminating data silos and creating a single source of truth
Empowering all users by democratizing data
Improving stakeholder and customer engagement
Optimizing processes and operations
Decreasing costs

Companies that create truly data-driven organizations are accelerating processes to deliver more timely insights to increase efficiency and revenue opportunities.

How Do I Bring Various Sources of Data Together to Support Our Analytics?

There are several methods and technologies to bring data sources together, so it is best to start with an assessment to understand your business. The right solution for one company may not be the right solution for yours.

A strategic analysis will uncover the specific challenges and best-fit solutions. At the same time, this can create consensus among team members on the chosen solutions.

How Do You Transform the Business into a Data-Driven Organization?

Creating a data-driven organization requires the appropriate technology and processes but you must also create a data culture throughout the enterprise. This doesn’t happen by accident.

Data culture must be intentional and driven by the people at the very top of the organization, who must embrace transformation and require data-driven decisions.

“Data can only take an organization so far. The real drivers are people.”– Gartner

Organizations must also put into place the processes to organize their data into a single source of truth that is accessible to everyone within the organization. This includes investing in the right self-service tools that support new technologies such as:

AI-driven insights
Cloud-based data lakes
Data virtualizations
Augmented analytics

Only then can you create a culture where data is easily accessible, insights are shared, and there is trust in the data across the organization.

What Does Data Transformation Mean?

Data transformation is part of an enterprise data and analytics initiative to support the decision-making process for diverse stakeholders. In many cases, this requires converting data from one or more sources into a new source that is cleansed, validated, and in an easy-to-use format for end users’ BI needs.

How Do I Diagnose and Correct Data Inconsistencies and Errors?

Ensuring data accuracy requires four components:

Data Discovery includes data and API connectors to automatically discover data sources and schemas. It also includes mapping processes from the data at the source and employing pattern detection capabilities.
Trust in the data involves automated data quality features to automatically detect data errors, ML data quality check suggestions, the ability to monitor data, and data cleansing processes.
Data synchronization to standardize, match, and merge data from multiple sources into a single cleansed record, and then send cleansed data back to the sources.
Data optimization that automates the data prep and cleansing processes for analytics and ensures that accurate data is accessible to all users within the organization.

What Are the Best Methods to Eliminate Data Silos in Our Business?

Eliminating data silos begins with defining the problems or impact that data silos have on the organization and the effect on the business. A Data Quality assessment can help document the current processes and tools, the key business drivers for a solution, and the expected success metrics.

The second step would be to audit the different management systems to determine how data is collected and how data is used within the organization. The results will help define the use cases and resources needed to implement a single source of truth.

The basic building blocks of a project to eliminate data silos within a business are:

Integrating all existing data management systems.
Cultivating a data culture that promotes transparency, sharing, and collaboration of data across the enterprise.
Establishing a data governance and data security plan.
Upgrading the company’s technology infrastructure to support the new data-driven requirements.

What Is Data Virtualization Versus a Data Warehouse to Make Data More Accessible?

Data virtualization establishes a logical integration and management of data sources. This results in greater flexibility in data integration, supports data transformation for analytics, and more efficiently meets the demands of the business to keep pace with the marketplace and competitors.

A data warehouse is a physical integration that requires the ETL of data from potentially multiple sources into a single repository before it can be made available to audiences for analytics. Solutions include data lakes, data virtualization, and data fabrics.

How Can the Cloud Help Me with My Information Management Challenges?

Implementation of a cloud strategy can significantly increase business agility and elasticity to meet changing markets and competitive situations. A cloud-first design supports greater agility to incorporate new or changing data requirements for the decision-making process and manage resources across an enterprise.

The cloud can facilitate increased collaboration and innovation for all employees regardless of where they are working, resulting in new competitive advantages, increased customer satisfaction, and heightened data security. At the same time, a well-designed cloud infrastructure enables an organization to streamline IT operations and reduce overall operating costs.

How to Find the Best Provider to Help You Implement the Best-Fit Solution

Finding the right provider to help you implement the best-fit solution for your business will require due diligence on your part. Work with a business that only focuses on data and analytics rather than a business that sells software, does only the strategy, or only the implementation. There isn’t anything out of the box or off the shelf to fix this problem.

Data and analytics are the DNA of KASH Tech, meaning that’s all we do. Our expertise is focused on solving these specific issues only. We provide end-to-end holistic services and own the entire process:

People, process, and technology — to find the best-fit solution that will help your organization streamline systems, trust the data, and build a data-driven business.

We are technology-agnostic. We have no agenda to sell specific software and no preconceived solution. Each client is given a solution that is unique to their challenges and needs.

We consider people and process as well as technology in the solution. This also means we become part of your business team to uncover what the challenges and needs are. Your problems become our problems and we define a solution around that.

We also build sustainable solutions. This means you won’t be dependent on us or other providers once the solution has been implemented. This is possible because KT does their consulting WITH the customer vs. OUTSIDE the customer’s team. The client has ownership in the success of the program.

Whether you work with KASH Tech or data and analytics services companies, here are the key things you should demand from any provider:

Shares the details of their methodology for solving the problem before paying for the services.
Has a defined process for uncovering the challenges that cause data silos and BI issues and is willing to share with you before signing up.
Includes people, processes, and technology as part of their solution. It takes a concerted effort in all three areas for success.
Has a robust and detailed assessment process that includes an in-depth analysis of your unique systems.
Fits your organization’s personality. You want a collaborative partnership rather than someone that has a canned solution that they force onto you.
Takes a technology-agnostic approach to create a custom solution that works best for you.

KASH Tech’s Four-phase Process to Produce Strategic Solutions

At KASH Tech, we follow a four-phase process to address clients’ needs to provide a custom solution to digital transformation challenges. Each client gets a Best-of-Fit solution for their unique configuration. This methodology includes a detailed analysis to provide a comprehensive strategy for implementation.

Discover how your organization can unlock advanced business intelligence, eliminate data silos, and create actionable business insights. Download the free KASH Tech Advanced Analytics Playbook: How to Unlock Breakthrough Business Insights.

If you’re ready to explore solutions, request a data and analytics discovery call from the KASH Tech team.